ChatGPT-4o vs Claude 4: Comprehensive Report and Comparison

ChatGPT-4o (GPT-4 “Omni”) is OpenAI’s multimodal flagship model introduced in May 2024. It extends GPT-4’s intelligence with capabilities across text, vision, and voice. Claude 4 refers to Anthropic’s fourth-generation AI models (Claude Opus 4 and Sonnet 4, launched May 2025) that emphasize advanced reasoning and coding performance. Below, we compare these two state-of-the-art AI assistants across key dimensions, including reasoning, creativity, coding, writing, factual accuracy, speed, context size, multimodal features, pricing, access, benchmarks, and user feedback.

Reasoning Ability

Both GPT-4o and Claude 4 are among the top performers in complex reasoning tasks. GPT-4o delivers “GPT-4-level” intelligence with notable improvements in reasoning across modalities. On academic benchmarks like Massive Multitask Language Understanding (MMLU), GPT-4o scores around 88.7% – slightly higher than the original GPT-4’s ~86.5%. Claude’s previous generation (Claude 3 Opus) reached roughly 86.8% on MMLU, and Claude 4 is reported to match or exceed these levels. In fact, Anthropic claims Claude Opus 4 “sets new standards in complex reasoning”. Internal evals show Claude Opus 4 hitting 87.4% on MMLU without tool use, essentially on par with GPT-4-class performance.

Claude 4 introduces an “extended thinking” mode that lets it use tools (e.g. web search) in multi-step reasoning. This means Claude can autonomously alternate between reasoning and external tool use to answer complex queries, potentially improving accuracy on “graduate-level” questions. GPT-4o does not natively have an internal tool-use loop (outside of plugin frameworks), but it has very strong built-in logical reasoning and world knowledge. On the Graduate-level Q&A (GPQA) benchmark, GPT-4o scored ~53.6%, slightly above Claude 3’s 50.4%. With Claude 4’s enhancements (and even higher GPQA Diamond scores when using its extended reasoning), the gap in pure reasoning is minimal. In sum, both models demonstrate excellent reasoning with GPT-4o holding a tiny edge in some evaluations, while Claude 4’s new tool-assisted reasoning offers powerful problem-solving on complex, multi-step tasks.

Creativity and Content Generation

When it comes to creative writing and content generation, both models are extremely capable, but they have distinct styles. Claude 4 is often lauded for its personable and empathetic tone. Users frequently describe Claude’s writing as warm, expressive, and more “human-like” in phrasing. It tends to produce imaginative, flowing narratives and can infuse emotional nuance effectively. In a head-to-head storytelling test, for example, Claude 4 Sonnet crafted a sci-fi story with vivid imagery and strong emotional stakes that “elevate[d] it beyond ChatGPT’s solid but less nuanced approach”. Claude’s default responses are typically longer and more detailed, which can be an advantage for thorough creative pieces or empathetic dialogues.

ChatGPT-4o, on the other hand, is known for its coherent and organized writing. It often provides more concise and structured outputs by default, unless prompted to elaborate. Its tone can be more neutral or “matter-of-fact,” which some might call a bit robotic, but this also means it generally stays on topic and avoids undue flourish unless asked. GPT-4o is highly versatile in style mimicry and can be directed to adopt various voices. In fact, it sometimes outperforms Claude in specific style emulation – one test found ChatGPT-4o nailed a casual Gen-Z social media style with precise slang and tone, whereas Claude’s attempt was creative but less spot-on with the slang usage. This indicates GPT-4o’s training on diverse internet text helps it imitate particular styles or dialects accurately when instructed.

For most creative tasks (storytelling, brainstorming, poetry, etc.), both are excellent. GPT-4o brings improvements in multilingual creativity (supporting ~50 languages with enhanced fluency) and even voice modulation (it can generate responses in different emotive speaking styles, including singing). Claude 4, meanwhile, often shines in open-ended creative brainstorming – users note it has a talent for generating “thoughtful and original” ideas and phrasing, avoiding repetitive language. In practice, the choice may come down to preference: Claude tends to be more expansive, emotionally attuned, and “freeform” in creative expression, while ChatGPT-4o is a bit more controlled, precise, and adaptable to specific stylistic instructions.

Coding and Software Development Tasks

Coding is a standout strength for both models, with Claude 4 in particular staking a claim as the new leader in this domain. Anthropic explicitly touts Claude Opus 4 as “the world’s best coding model,” noting it achieved state-of-the-art results on internal software engineering benchmarks. For example, Claude Opus 4 leads on the SWE-Bench (Software Engineering benchmark), solving 72.5% of real coding tasks (and up to ~79% with advanced techniques) – outperforming OpenAI’s GPT-4 and even Google’s latest Gemini on that benchmark. It also tops the Terminal-Bench (a benchmark for long-running coding workflows) with 43.2%. These results align with feedback from developers: Claude 4 is highly capable of writing correct, complex code and maintaining context over long sessions. It can sustain multi-file projects for hours and apply changes reliably across a large codebase. Early partners report that Claude 4 improved precision on complex code edits and debugging tasks that earlier models struggled with. In short, Claude 4’s coding prowess is cutting-edge, and even its “instant” variant (Sonnet 4) scores a strong 72.7% on SWE-Bench, making it very effective for coding help.

 Claude 4 models lead on a software engineering benchmark (SWE-Bench). Both Claude Opus 4 and Sonnet 4 significantly outperform OpenAI’s GPT-4 on this coding test.

ChatGPT’s GPT-4 models have long been excellent at programming tasks as well. GPT-4 (original) was a top performer on coding challenges (e.g. ~80-85% on HumanEval Python problems) and GPT-4o has improved further, reportedly solving about 90% of HumanEval correctly. This edges out Claude 3’s ~85% on the same test. In real use, developers praise GPT-4/GPT-4o for its reliability in code generation, detailed explanations, and ability to debug code step-by-step. GPT-4o can generate new code, analyze existing code, and even handle some code-based reasoning in conjunction with its vision (e.g. describing what a piece of code does from a screenshot). OpenAI has also integrated GPT-4 into tools like GitHub Copilot, and GPT-4o introduced structured code output modes (JSON formatting of code responses) to better integrate into dev workflows.

The practical differences: Claude often produces code that is very clean and thoughtfully commented; users have found Claude’s first attempt is frequently “nearly bug-free” in simple scenarios. Its large context (200K tokens) means Claude can ingest an entire codebase or lengthy logs and still reason about them, providing refactoring or multi-file edits with great continuity. Claude 4 also has a new “Claude Code” IDE integration, allowing it to directly suggest edits in VS Code/JetBrains and even run continuous integration tests via an SDK. GPT-4o’s context is also large (128K tokens), though a bit smaller, and it lacks a first-party IDE plugin from OpenAI (developers typically use it through third-party plugins or the ChatGPT UI). One advantage on OpenAI’s side is the Code Interpreter/Advanced Data Analysis tool in ChatGPT, which lets GPT-4 run Python code and work with files – effectively allowing it to execute code and verify outputs in a sandbox. Claude doesn’t natively execute code within the chat UI (outside of its API tool mode for developers), so ChatGPT Plus users might find GPT-4o more handy for data analysis or code that needs running tests within the conversation.

Overall, Claude 4 currently holds a slight edge for pure coding generation and handling large-scale projects, thanks to its coding-optimized training and longer focus. GPT-4o is not far behind – it remains extremely capable at coding and offers useful interactive tools (like actually running code via plugins) that Claude lacks in the chat interface. Many developers employ both: for instance, using Claude to navigate and modify very large codebases, and ChatGPT to execute code or confirm outputs. Both models have been adopted in real developer workflows – notably, GitHub plans to use Claude 4 Sonnet to power a new coding assistant in Copilot, highlighting Claude’s strength in agent-like coding tasks.

Writing: Long-Form, Summarization, and Style Imitation

In extended writing and summarization tasks, GPT-4o and Claude 4 again are top-tier performers. They can both produce well-structured essays, articles, or reports, and condense lengthy material into concise summaries. However, Claude has a natural advantage in long-form content due to its massive context window. With the ability to handle up to 200,000 tokens of context, Claude 4 can ingest very large documents or multi-chapter texts and summarize or analyze them in one go. This makes Claude extremely useful for summarizing long PDFs, transcripts, or even books. Users often report that Claude’s summaries are accurate and nuanced, capturing key points in a human-like narrative style. One programmer who compared the two noted Claude’s summary of a personal finance PDF was more precise and “smart, human-like” in tone, whereas GPT-4’s summary missed details and felt more robotic. Claude also tends to preserve the original document’s context faithfully, thanks to its focus on not losing track of details within its larger window.

ChatGPT-4o, with a 128K token context, is also capable of long inputs – it can maintain coherence over very lengthy conversations or documents – but in practice this is often utilized via the API or special “long” versions. In the ChatGPT consumer app, GPT-4o is typically limited to shorter windows (unless using the API with 128k model). That said, GPT-4 and 4o have proven exceptionally strong at summarization even on shorter contexts. GPT-4o scored in the mid-80s on summarization benchmarks, slightly above Claude-3’s performance. It concisely distills information and tends to stick closely to facts from the source. If summarizing a chapter or an article, ChatGPT often produces a more to-the-point summary by default, whereas Claude might give a more narrative recap including context or implications. Both approaches can be tailored via instructions (you can ask either to be more detailed or more brief).

For style matching and tone, both models are highly flexible. Claude is praised for adapting to a given writing style when properly guided – for instance, it can take an outline and expand it into a well-written piece, adjusting formality or voice as requested. In one test, Claude 3.5 did a great job making a piece less formal and more approachable when asked, more naturally than ChatGPT in that instance. Claude’s writing style can vary run to run (injecting synonyms or rephrasing to avoid monotony), which many see as a plus for creativity. ChatGPT-4o can also emulate styles (from Shakespearean prose to casual blogging or technical jargon) and benefits from OpenAI’s custom instructions feature where a user can set a persistent “writing style” for it to follow. In direct style challenges, we’ve seen mixed results: ChatGPT won a slang-heavy tone contest, while Claude excelled at a balanced professional tone in other cases.

In sum, both are excellent writing assistants. Claude’s strengths lie in handling very large texts, maintaining an engaging tone, and producing rich, flowing prose. ChatGPT-4o excels in crisp, factual writing and can imitate specific voices or formats with high precision. Importantly, both have strong “memory” for context within a document – GPT-4o improved its ability to remember and reference earlier parts of a long document or conversation, and Claude 4 introduced enhanced memory features (like writing “memory files” when given tools) to keep track of facts over very long interactions. Writers may find Claude feels more like an expansive co-author at times, whereas ChatGPT can function like an ultra-smart editor or fact-checker to tighten and refine text. Using them together is also popular: for example, one might use Claude to generate a first draft and then ChatGPT-4o to proofread and adjust the style or vice versa.

Factual Accuracy and Hallucination Rate

Ensuring factual accuracy is a crucial aspect of these models. Both GPT-4o and Claude 4 represent improvements over previous models in reducing hallucinations (fabricated or incorrect statements), but neither is perfect. OpenAI has explicitly worked on “reducing the generation of incorrect or misleading information” in GPT-4o. The model was trained with refined methods to minimize ungrounded inference, and its system card notes that GPT-4o is designed to be safer and more factually consistent than prior versions. Anecdotally, many users find ChatGPT-4 (and 4o) to be highly reliable on factual queries; it often provides sources or refuses to guess if it’s not confident. In benchmark evaluations, GPT-4 models generally scored top marks on knowledge and reasoning tests, suggesting strong factual grounding (e.g., one academic assessment cited GPT-4’s factual success rate at ~84%, significantly higher than many models). GPT-4o continues this trend with incremental gains in many areas.

Claude has also improved in factual accuracy, though its approach differs. Claude uses a “Constitutional AI” alignment technique which can sometimes lead it to double-check itself or add disclaimers. Users report that Claude 3/4 is less likely to outright refuse an answer, but if it’s unsure, it may produce a guess couched in a very detailed explanation. This can be a double-edged sword: at times Claude will produce a very convincing but subtly incorrect answer (a hallucination with confident tone), whereas ChatGPT might more frequently say “I’m not sure” or give a partial answer. However, community feedback suggests that Claude’s factual accuracy in many practical tasks is on par with GPT-4. For instance, in summarization tasks, Claude 3.5 was noted to avoid factual errors that GPT-4 made. And in math word problems or multi-step reasoning, Claude 3/4’s chain-of-thought approach can catch mistakes (Claude 3 scored ~95% vs GPT-4’s 92% on a set of elementary math problems in one informal test).

On the flip side, GPT-4o underwent red-teaming to cut down hallucinations and had fine-tuning to be more cautious with facts. The results are evident in some evaluations: one comparison found GPT-4.5 (an updated GPT-4) produced significantly fewer hallucinations and more consistent facts than Claude 3.7 in advanced testing. Additionally, a Hallucination leaderboard by HuggingFace showed GPT-4o-mini and GPT-4 Turbo among top performers with very low hallucination rates (near 1.7%) – although details of that metric aside, it indicates OpenAI’s models are highly tuned against making things up. Anthropic’s Claude 4 has likely closed the gap further: Anthropic focuses on “groundedness” and even introduced a feature in Claude 4 where if its chain-of-thought is too long, it uses a smaller model to summarize its own reasoning to stay on track. This meta-cognitive step is meant to prevent the model from drifting into fantasy during extended reasoning.

In practical use, both models can still hallucinate under certain conditions (especially with ambiguous or niche queries). GPT-4o might be slightly better at saying “I don’t know” or sticking to known facts, whereas Claude might fabricate an answer in its eagerness to be helpful if not monitored. Users have found that providing references or asking the model to cite sources can mitigate hallucinations. OpenAI’s Bing integration and OpenAI Plugins allow GPT-4o to fetch real data, reducing guesswork, while Anthropic’s tool use (web search, etc.) can help Claude verify info if enabled. Ultimately, neither is immune to errors: careful prompting and cross-checking are advised for critical factual tasks. On the whole, GPT-4o is perceived as very slightly more factually reliable by benchmarks, whereas Claude often impresses users with its detailed and usually correct outputs in real-world scenarios, only occasionally introducing subtle inaccuracies.

Speed and Latency

Speed is an area where these newer models have made big strides. GPT-4o is significantly faster than the original GPT-4, which had a reputation for being relatively slow in interactive chat. OpenAI optimized GPT-4o for real-time responsiveness – it can handle voice conversations with an average response time around 320 milliseconds, nearly human-level turn-taking speed. In text terms, GPT-4o can output roughly 110 tokens per second, which is about 3× faster than GPT-4 Turbo (the late-2023 version). This improved throughput also outpaced many competitors in tests, including Anthropic’s Claude 3 Opus. Users of ChatGPT-4o notice that it starts generating answers almost immediately and maintains a steady, quick stream even for long answers. The model can even be interrupted and respond adaptively in real-time in voice mode, underscoring its low latency design.

Claude 4 also delivers fast performance, especially in its “instant” mode (Claude Sonnet 4). Anthropic describes Claude 4 models as hybrid with two modes: near-instant responses vs. extended thinking. In normal queries, Claude 4 (Sonnet) is very snappy – often as fast as ChatGPT or faster for straightforward Q&A. Users have observed that Claude can produce large responses extremely quickly when not doing heavy reasoning, sometimes finishing an essay-length answer a bit ahead of GPT-4. However, when Claude engages its extended thinking (e.g. using tools or doing very complex multi-step solutions), it deliberately slows down to think through steps. This can introduce some latency for those specific tasks (it might take a short pause to perform a web search or run a code tool in the background before continuing its answer). The extended mode is opt-in for developers and for certain prompts, so average chat users won’t notice much delay unless the question is very complex. Notably, Claude 4’s “parallel tool use” allows it to perform background operations concurrently, which can mitigate some speed loss by multitasking reasoning steps.

In head-to-head use, ChatGPT-4o and Claude 4 Sonnet both feel responsive and interactive. For typical conversation or short prompts, both yield a near real-time stream of tokens. If anything, GPT-4o might have an edge in consistency of high token-per-second generation under load (as evidenced by OpenAI’s benchmarks). Claude’s advantage is that it can sometimes complete a thought in fewer tokens (due to a more verbose thinking process hidden or pre-optimized), which means it might reach the conclusion slightly faster in complex cases. On very large inputs, Claude may also take a bit longer to ingest all 200k tokens of context upfront, whereas GPT-4o’s 128k context, if utilized, also requires significant processing but we have less public data on its long-input latency.

From an API perspective, OpenAI also increased GPT-4o’s throughput limits – it has higher rate limits than GPT-4 Turbo, meaning applications can send more requests per minute. Anthropic similarly offers higher-rate modes for Claude in the Max plans (see Pricing), but single-query speed is generally comparable. In summary, both models are fast enough for most use cases, with GPT-4o being a clear improvement over older GPT-4 in speed and Claude 4 offering instant responses for everyday prompts and a slower, methodical mode for tougher tasks. Neither will keep you waiting long in interactive chat, and both support streaming outputs that let you start reading the answer as it’s generated.

Context Window and Multimodal Capabilities

One of the most dramatic differences in these models is their context window and supported input/output modalities:

• Context Window: GPT-4o supports up to 128,000 tokens of context (input + output combined). This huge context length means it can maintain very long conversations or analyze lengthy materials. In practice, GPT-4o’s default usage in ChatGPT might not always expose the full 128k, but the model is designed for it (and an API variant or “long” mode can handle it). Claude 4 sets a new record with a 200,000-token context window – currently the largest among major models. This allows Claude to handle hundreds of pages of text in one prompt without losing coherence. For example, one could give Claude an entire novel (~150k tokens) and ask detailed questions about it. Claude 4’s large context is a continuation of Anthropic’s focus (Claude 2 offered 100k context already). In practical terms, both models can retain context over very extensive interactions, but Claude’s window is ~1.5× bigger, giving it an edge for the absolute longest documents.

• Multimodal Input: GPT-4o is a true “omni” model, natively accepting text, images, audio, and even video as input. You can feed it a picture (e.g. a chart, a photograph) and ask questions, or speak to it with your voice, or even provide a short video clip for analysis. GPT-4o was trained end-to-end on multiple modalities, meaning the single model handles them seamlessly. For instance, it can look at a screenshot of code and explain it, or listen to spoken language and respond. Claude 4 accepts text and images as inputs. Anthropic added image understanding capabilities (so you can upload an image for Claude to describe or interpret). As of May 2025, Claude also introduced a voice mode for input: on mobile apps, users can speak to Claude and it will transcribe their speech to text (using an integrated speech-to-text) and respond by voice output. However, this is more of an interface feature – the Claude model itself still processes text (the audio is converted to text for Claude, unlike GPT-4o which directly processes audio in the neural network). In short, GPT-4o has broader native multimodal capacities (including audio and even video frames as input), whereas Claude 4 covers vision and voice via external handling.

• Multimodal Output: GPT-4o can generate text, and also produce audio (speech) and images as outputs from the same model. In ChatGPT, GPT-4o powers the voice replies (with various voice styles) where it synthesizes speech that sounds human-like. Remarkably, GPT-4o also has built-in image generation ability. Unlike GPT-4 Turbo which had to invoke DALL·E for images, GPT-4o can directly create images from prompts (this was shown in OpenAI’s demos and mentioned in documentation). This essentially bakes a DALL·E3-level capability into the model. Claude 4, in contrast, outputs text only. When using voice mode, Claude’s text response is then converted to spoken audio by the app, but the model itself doesn’t generate audio waveform. Claude currently has no image generation feature – it can describe an image you give it, but it cannot produce a new image on its own. Anthropic’s focus has been more on text modalities and reliable tool use, rather than turning Claude into an image or audio generator.

To summarize Context & Multimodality: Claude 4 has the larger context window (200k vs 128k), making it king for very long textual contexts. GPT-4o is more broadly multimodal, handling audio and visual tasks in one system. If your use case involves mixing voice, images, and text fluidly (e.g. talking to an assistant that can see and speak), GPT-4o offers that out-of-the-box. If you need to feed in an extremely large text (like whole databases or lengthy legal briefs), Claude 4’s expanded context is a big advantage. Notably, both models support image inputs for analysis (e.g. “What’s in this photo?” works on both), and both now support voice conversation (ChatGPT had voice since late 2023, Claude followed in 2025 with its own voice beta). For developers, each platform provides API access to these modes: OpenAI’s API for GPT-4o includes image and audio endpoints (with some currently limited release for audio), and Anthropic’s API/SDK similarly allows image inputs and will be integrating voice.

Cost and Pricing Models (API & Consumer Plans)

OpenAI (ChatGPT-4o) Pricing: OpenAI’s pricing strategy for GPT-4o has been to make it more affordable than earlier GPT-4 models. In the API, GPT-4o is roughly half the price of GPT-4 Turbo per token. To illustrate, GPT-4 Turbo (32k) was around $0.06 per 1K output tokens; GPT-4o comes in at about $0.03 per 1K output tokens for the same context size (50% cheaper). OpenAI hasn’t publicly listed a simple price table for GPT-4o as a whole, but we do know GPT-4o mini (the smaller, faster variant) is extremely cheap – $0.15 per million input tokens and $0.60 per million output tokens. That translates to an astonishing $0.00015 per 1K tokens in, $0.0006 per 1K out, making GPT-4o mini 10× cheaper than even GPT-3.5 in usage. This mini model is used for high-volume or budget-conscious applications (with lower performance than full GPT-4o). The full GPT-4o model’s token pricing might be on the order of $0.015 per 1K input and $0.03 per 1K output (approximation based on “half of GPT-4”), but exact numbers would come from OpenAI’s pricing page. Nonetheless, OpenAI emphasizes that GPT-4o offers higher throughput at lower cost to developers than previous GPT-4 versions.

On the consumer side, OpenAI offers ChatGPT at multiple tiers: Free, Plus ($20/month), and as of 2025, a Pro tier (~$200/month). The free tier now actually includes GPT-4o (at least the “mini” model) for everyone. This was a major shift – starting May 2024, ChatGPT free users get access to GPT-4o capabilities with some limitations (namely, a lower rate limit on messages). OpenAI says free ChatGPT will automatically switch to GPT-3.5 if the user hits the GPT-4o rate limit. The free plan also gained previously paywalled features like file uploads, persistent memory, and web browsing after the GPT-4o launch, which significantly increased its value. ChatGPT Plus ($20/month) gives uninterrupted access to GPT-4o (full model) with higher message limits (5× higher usage caps than free). Plus users also get faster response priority and early access to new features (like GPT-4 vision, voice, plugins, etc.). For power users, OpenAI introduced ChatGPT Pro at $200/month, which provides essentially unlimited usage of GPT-4 (no cap on messages, highest priority speeds). This tier is ideal for those who use ChatGPT extensively or for business purposes; it parallels what Anthropic is doing with Claude Max. There are also Team and Enterprise plans for organizations (ChatGPT Enterprise has custom pricing, enhanced privacy, longer context up to 32k, and admin controls).

Anthropic (Claude 4) Pricing: Anthropic’s API pricing is structured by model type. Claude 4 comes in two flavors for API use: Claude Opus 4 (the most powerful) and Claude Sonnet 4 (high-performance but lighter). Notably, pricing remained the same as their previous generation: Claude Opus 4 is $15 per million input tokens and $75 per million output tokens. This works out to $0.015/1K tokens in, $0.075/1K out. Claude Sonnet 4 is $3 per million input and $15 per million output (i.e. $0.003/1K in, $0.015/1K out). These rates mean that Opus (the top model) is about 2–3× the cost of OpenAI’s GPT-4o for output tokens, whereas Sonnet 4 is roughly on par or cheaper. For example, generating 1,000 tokens of output costs ~$0.03 with GPT-4o vs $0.075 with Claude Opus 4, but only $0.015 with Claude Sonnet 4. Many developers might use Sonnet for faster/cheaper tasks and call Opus for the hardest problems. Both models are available via API, and also through cloud platforms like AWS Bedrock and Google Vertex AI with the same pricing.

For consumer subscriptions, Anthropic offers Claude.ai plans in a tiered system:

• Free: Anyone can use Claude 4 Sonnet for free at claude.ai or the mobile apps, with a daily message limit (previously Claude 2 free allowed something like 1–5 prompts every 8 hours; Claude 4 free likely has a similar quota). Free users get Claude Sonnet 4 access, which is impressive since that model is quite powerful – Anthropic essentially gave the general public a taste of their latest model at no cost.

• Claude Pro ($20/month): This roughly corresponds to ChatGPT Plus. Claude Pro gives a higher usage limit (approximately 5× the free messages per day, as reported). It includes priority access to Claude’s latest models (Sonnet 4, and likely also Opus 4 for some queries), though it appears Opus 4 usage might be metered even for Pro (Anthropic might restrict how many Opus-level generations a Pro user can do because Opus is more expensive). The Pro plan is aimed at regular individual users and is similarly priced to ChatGPT Plus.

• Claude Max ($100 or $200/month): In April 2025, Anthropic launched these higher tiers to cater to power users and professionals. Claude Max $100/month gives ~5× the Pro usage limits, and Claude Max $200/month gives ~20× the Pro limits. These plans also likely guarantee access to the highest-end model (Opus 4) with priority. Essentially, for $200 you can use Claude almost as freely as you want (though Anthropic notably still has some cap; they don’t offer truly unlimited, but the cap is very high). The $200 Claude Max tier is Anthropic’s answer to OpenAI’s ChatGPT Pro at the same price. Both are targeting enthusiasts, developers, or businesses that heavily rely on the AI and need the top performance with minimal throttling.

• Business and Others: Anthropic also offers Claude Team and Enterprise plans (with custom pricing) and even specialized plans like Claude for Education. Enterprise customers can get even larger quotas, 24/7 support, data privacy guarantees, etc.

Overall, OpenAI’s GPT-4o API is cheaper per token for the highest-end model, but Anthropic offers a very competitive lower-cost model (Sonnet) that undercuts OpenAI’s full model pricing. In consumer plans, both have a free tier and a ~$20 tier for broad access. OpenAI’s introduction of a $200 Pro plan for unlimited use was quickly mirrored by Anthropic’s Max $200 plan. One difference: OpenAI Plus is limited by a fairly tight message cap (e.g. 50 GPT-4 messages per 3 hours historically), whereas Anthropic’s Pro is limited by daily quota (exact numbers vary, but users often hit Claude’s cap if they have extremely long sessions). Now with Max, a user can get much higher limits on Claude. OpenAI’s $200 ChatGPT Pro basically removes caps entirely, which Anthropic doesn’t yet do (they hinted they might consider even pricier unlimited plans later).

From a developer’s view, cost might also factor in context length: processing 100k tokens context is expensive on any API. If one regularly needs 150k token contexts, it might be more cost-effective with Claude (since it can do it in one shot, whereas GPT-4o might require chunking or summarizing due to 128k limit). But if one just needs lots of short queries, GPT-4o’s token price advantage (and the existence of GPT-4o mini at ultra-low cost) can save significant money.

Free vs Paid Access

Both OpenAI and Anthropic provide ways to use these advanced models for free, with the trade-off being usage limits and possibly slightly reduced capacity.

ChatGPT (GPT-4o) Free: The free version of ChatGPT now uses GPT-4o “mini” as the default assistant. This means free users are effectively getting GPT-4 level quality (far better than the old GPT-3.5 model) for casual use. However, free usage is throttled: OpenAI imposes a limit on how many messages you can send with GPT-4o in a certain time. If you hit that, ChatGPT will automatically respond using the older GPT-3.5 model until some cooldown resets. Also, certain features like the new voice conversation and image uploads rolled out to free users only after Plus users had them for a while. But as of mid-2024, OpenAI actually unlocked web browsing, image uploads, and chat history “memory” for free accounts, which was a generous move. So a free ChatGPT user can do a lot, just with slower rates and no guaranteed availability during peak times. That said, at peak load OpenAI might prioritize Plus users, meaning free users could see slower responses occasionally.

Claude Instant (Free): Anthropic allows anyone to sign up at claude.ai and chat with Claude 4 (Sonnet) for free. The free tier has a daily message quota (for example, previously it was 100 messages per 18 hours on Claude 2; it may have changed with Claude 4 but likely in that ballpark). Also, free Claude might have a lower maximum context one can use per prompt than paid (perhaps free users can use, say, 10k tokens per prompt, whereas paid can go full 100k+). Anthropic has been fairly generous, even enabling free users to try new features like 100k context and Claude’s latest model, albeit in limited amounts. Notably, Claude 4 Sonnet is available to free users as an “instant upgrade” from the old Claude 3.7. This means the baseline quality for free users on Claude is extremely high (comparable to GPT-4 class). The main limitation is quantity: heavy users will quickly exhaust the free quota. Many enthusiasts maintain both a free Claude and a free ChatGPT account to toggle between them when one hits a limit.

Plus vs Pro (OpenAI): Upgrading to ChatGPT Plus ($20) gets you the full power of GPT-4o without frequent throttling. Plus users have priority, meaning even at busy times their queries are answered fast. Plus also unlocks GPT-4’s higher limits (e.g. 50 messages / 3 hours or whatever current policy is) and features like the plug-in store, Code Interpreter, and custom instruction settings. For most individuals and professionals, Plus suffices. Only extremely heavy users or small businesses likely need ChatGPT Pro ($200), which lifts the message cap entirely and possibly gives access to GPT-4 32k context model on demand. Pro also might include early alpha features and guaranteed uptime. Essentially, Plus is “GPT-4 on a diet” whereas Pro is “all-you-can-eat GPT-4.” OpenAI also has ChatGPT Enterprise with unlimited use, 32k context, and data encryption – but that’s a separate product for organizations.

Claude Pro vs Max: Claude Pro ($20) similarly gives the average user more than enough usage (5× free limit, as mentioned) and access to Claude’s top models. Anthropic’s docs note that Pro, Max, Team, and Enterprise plans all include both Claude 4 models (Sonnet and Opus) and the new extended reasoning features. So as a Pro subscriber, you can actually tap into Claude Opus 4 for the really tough queries – though it might count more against your usage. The Max plans ($100/$200) are for power users; they raise the usage by 5× and 20×, respectively, which is huge if you are running many queries or building a project on Claude. Unlike OpenAI, Anthropic’s Max $200 plan still isn’t completely “unlimited”, but 20× the standard Pro usage is effectively very high (perhaps thousands of messages per day). Anthropic currently does not offer an “unlimited” plan, and a representative hinted they might consider higher tiers in the future if needed.

One key difference: OpenAI’s ecosystem vs Anthropic’s accessibility. ChatGPT Plus gives you access to multiple GPT-4 variants (like you can choose GPT-4 or older GPT-3.5 as needed, and presumably GPT-4o and GPT-4o-32k if available). Claude’s interface, on the other hand, typically just uses the best available model and manages it for you – free gets Sonnet 4, paid gets Sonnet 4 and Opus 4 dynamically. OpenAI has plugins and the code execution mode for Plus users, features which Anthropic’s Claude (even Pro/Max) doesn’t directly have in the chat UI. Claude is somewhat more integrated into other platforms, though – for instance, you can use Claude for free on Poe.com (Quora’s chatbot hub) albeit with some daily cap, and Claude is also offered in some third-party apps (Jasper, Notion AI as an option, etc.). ChatGPT’s official free interface is only on OpenAI’s site or apps, but its API is widely integrated into many products (Bing Chat, Office 365 Copilot, etc.).

From a user feedback perspective, many enthusiasts actually maintain subscriptions to both services. They use Claude for as much as possible due to its strengths, until they hit limits, then switch to ChatGPT Plus for additional queries. Each platform’s paid plan is relatively affordable for what it offers (at $20/month, it can be easily worth it for heavy daily use). The free tiers are great for casual users or those who want to try before buying. In 2025, the landscape is such that basic AI assistant functionality is free (both OpenAI and Anthropic let you chat with an advanced model at no cost), but the full, unrestricted experience costs ~$20/month, and the power-user experience can cost $100–$200/month.

Benchmark Results and Performance Evaluations

To objectively compare these models, we can look at benchmark tests and head-to-head evaluations:

• MMLU (Massive Multitask Language Understanding): This is a measure of knowledge across 57 subjects. GPT-4o scored 88.7 on MMLU, slightly improving on GPT-4’s ~86.5. Claude 3.7 Sonnet had around 79.0, and Claude 3 Opus ~86.8. Claude 4 was reported at 87.4 (Opus 4, no extended thinking), indicating it has reached parity with GPT-4 level on this broad knowledge test. In essence, both GPT-4o and Claude 4 answer academic questions at roughly an undergraduate A- level performance.

• HumanEval (Coding test): Measures correctness on programming challenges. GPT-4o achieves about 90.2% pass rate, which is excellent (original GPT-4 was ~85-88%). Claude 3 Opus was ~84.9% on the same, a bit behind GPT-4o. Claude 4’s coding benchmarks (SWE-bench) suggest it is similarly strong, if not stronger in realistic coding tasks – since Claude 4 solved ~72.5% of tasks vs OpenAI’s best around 69% on one software benchmark. Overall both are top-tier for coding, but benchmarks like HumanEval give GPT-4o a slight edge in pure code writing accuracy, whereas complex coding benchmarks tilt toward Claude 4.

• Mathematical Reasoning (MATH, MGSM etc.): On the MATH competition benchmark, GPT-4o scored ~76.6, and on Multilingual Grade School Math (MGSM) it scored 90.5. Claude-3 Opus was a bit lower on MATH (60.1) and actually slightly higher on MGSM (90.7). These small differences show that performance is task-specific; GPT-4o leads on MATH, Claude led by a hair on multilingual math. We can expect Claude 4 to have improved further, possibly closing the gap in pure math.

• Other Knowledge Benchmarks (DROP, BBH, etc.): OpenAI reported GPT-4o beat GPT-4 Turbo on benchmarks like BBH (Big Bench Hard) and showed a few-point improvements across the board. Interestingly, GPT-4o slightly lost to GPT-4 Turbo on the DROP reading comprehension test (83.4 vs ~85), showing no model wins everything. Claude’s strengths often lie in reading and reasoning (it scored ~83.1 on DROP, comparable to GPT-4o’s 83.4). So comprehensively, both models sit at the top of most benchmark leaderboards, trading the #1 position depending on the specific task.

• Chatbot Arena (LMSYS) Results: The LMSYS Chatbot Arena is a platform where humans vote on model outputs in paired battles. GPT-4 variants dominated for a long time, but in March 2024 Anthropic’s Claude 3 Opus briefly took the #1 spot, narrowly surpassing GPT-4 in Elo rating. The difference was small (Claude’s win rate was roughly 50.2% vs GPT-4 in pairwise, essentially a tie), but it marked the first time GPT-4 had been dethroned on that leaderboard. By mid-2024, after GPT-4o’s release, the tables turned again – GPT-4o rose to the top, with one report saying it held about a 65% average win rate against all other models in Arena comparisons. Claude 3 Opus remained in the top tier as well, among the leaders. These crowd-sourced rankings indicate that GPT-4o and Claude are very close in overall quality. A 65% win rate for GPT-4o means it won comfortably vs many models but likely was roughly tied with the next best (perhaps Google’s Gemini or Claude). With Claude 4’s debut, it wouldn’t be surprising to see it challenge GPT-4o again in such head-to-head arenas. (As of the latest public Arena data, closed models like Claude 4 may not yet be included, but anecdotal tests suggest Claude 4 is indeed on par or better in many scenarios – as also reflected in one-on-one testing by journalists, covered next.)

• Real-world 7-Prompt Showdowns: Tech reviewers at Tom’s Guide conducted direct face-offs with a series of prompts. In a Claude 4 Sonnet vs ChatGPT-4o (May 2025) test covering 7 diverse tasks, Claude 4 was the overall winner. Claude won in categories like productivity planning, storytelling, brainstorming ideas, emotional support, and critical analysis. There was one tie (math problem solving) and ChatGPT-4o won one round (imitating Gen-Z social media style). The reviewer noted Claude’s answers often better addressed the prompt with deeper insight or empathy, whereas ChatGPT sometimes was more concise or straightforward. In another comparison a few months earlier (Claude 3.7 vs GPT-4o), ChatGPT-4o had dominated, “leaving the other in the dust,” according to the article headline, showing how the balance can shift with model upgrades. By late 2024/early 2025, many saw Claude 3.5/3.7 as nearly equal to GPT-4 – one user even remarked that going back to GPT-4 after using Claude felt like reverting to GPT-3.5. Now with Claude 4, Anthropic has closed any remaining gap and in certain use cases edged ahead.

In summary, benchmarks and evaluations paint a picture of two evenly matched heavyweights. GPT-4o tends to slightly lead in aggregated quantitative benchmarks (owing to OpenAI’s extensive fine-tuning and perhaps a larger parameter count), while Claude 4 often wins qualitative and user-experience-focused comparisons (owing to its detailed, human-like responses and longer context capabilities). Both achieve top-tier results on standard tests like MMLU, coding, etc., far above most other models in 2024–2025. It’s fair to call them the premier AI models of the moment, with performance differences of only a few percentage points on most metrics.

Real-World Use Cases and User Experience

Finally, looking beyond tests, how do ChatGPT-4o and Claude 4 differ in daily use and what do users say about them?

Use Case Fit:

• ChatGPT-4o excels as a general-purpose assistant integrated into various tools. It’s deeply embedded in the Microsoft ecosystem (Bing Chat, Office Copilot) and has a plugin/store system enabling countless use cases – from travel booking, to coding with terminal access, to searching the web on demand. If you need an AI that can interface with other services (via plugins or API calls) and reliably follow instructions, ChatGPT is a great choice. It’s also the go-to for scenarios requiring multiple modalities in one workflow (e.g. speak a question, show an image, get both a spoken answer and a generated chart). Many users use ChatGPT for learning and research, benefiting from its factual accuracy and the ability to have it cite sources (especially when using the browsing tool or custom instructions to get references).

• Claude 4 has carved out a niche among writers, researchers, and developers dealing with large volumes of text. Its 200k context means students and lawyers love it for digesting long PDFs (research papers, legal contracts, etc.) in one shot – Claude can output a thorough summary or answer specific questions with all that context loaded. It’s also popular for brainstorming and personal assistance: people mention Claude feels more like “a colleague or friend” in conversation due to its empathetic style. For advice, journaling, or creative collaboration (like co-writing a story), Claude’s longer, often more thoughtful responses can be very helpful. Programmers use Claude to analyze big codebases or log files that wouldn’t fit in other models, and they appreciate that Claude often suggests correct code fixes on the first try. One developer gave the example that Claude produced bug-free code and accurate summaries, whereas GPT-4 had minor mistakes, shifting his preference toward Claude.

Tone and Interaction: Users frequently comment on the personality and feel of each AI. Claude is described as friendly, enthusiastic, and even humorous at times. It often peppers responses with empathy (“I understand how you feel…”) and positive encouragement. Some find this endearing and more human. For instance, in providing emotional support or counseling-like responses, Claude was found to mirror a thoughtful friend, offering comfort in a very genuine tone – this was noted as a win in the emotional support prompt test. ChatGPT, while generally polite and helpful, has a more formal and concise demeanor. It sticks to the point and avoids as much emotional language unless asked. Some users prefer this no-nonsense approach as it feels efficient and professional. Others might say ChatGPT can be too terse or clinical at times. Notably, OpenAI has added features (like custom instructions) to let users personalize ChatGPT’s style, so one could instruct it to be more cheerful or more elaborate if desired – narrowing this gap.

Refusal and Safety Behavior: Both models have safety filters, but they handle them a bit differently. ChatGPT (especially the OpenAI model) tends to give a quick refusal if a request violates content policy, often with a short apology and statement that it cannot comply. Claude also refuses disallowed content, but its refusals might come with more explanation or an attempt to be helpful within limits. Some users found Claude to be slightly more lenient in edge cases, or at least more verbose about why it won’t do something. For example, Claude might say: “I’m sorry, I can’t help with that because …” and sometimes it might offer a toned-down alternative. ChatGPT’s rules became stricter over time, but GPT-4o’s system message allows it to do tasks like mild role-play or discuss certain sensitive topics in a factual manner. In practice, both are firmly constrained on obvious disallowed content (hate, self-harm encouragement, illicit instructions, etc., will be refused by both). If anything, advanced users noted that Claude could sometimes be convinced to discuss slightly edgy content with clever prompts, but Anthropic likely tightened this with Claude 4. OpenAI’s model is more likely to just say no and not continue the discussion if you hit a boundary.

Reliability and Robustness: In real-world usage, consistency matters. GPT-4o is often praised for staying on track – it rarely diverts from the user’s question and follows instructions closely. The system OpenAI has (with role messages and user instructions) generally keeps ChatGPT focused. Claude is highly capable but some have observed it can get “too eager” and produce very lengthy answers even if not asked, or include tangents. This is not necessarily negative – when you want a comprehensive answer, Claude provides it. But if you prefer brevity, you might need to explicitly ask Claude to be brief. That said, Anthropic improved Claude 4’s steerability, so it now follows instructions about style/length much better than before. For multi-turn conversations, both maintain context well, but with extremely long threads, users have noticed GPT-4 (and now 4o) might start dropping some earlier context (especially on free plan smaller window) while Claude with its larger window retains details. In a long interactive session (say 100+ exchanges), Claude’s continuity might shine, whereas ChatGPT might need the user to recap or it might accidentally contradict something said much earlier.

User Feedback Sentiment: It’s instructive to note sentiments from community forums. On Reddit communities, a common refrain was “Claude is better in almost every way except the limits”. Enthusiasts who have access to both often love Claude’s output quality but lament the daily cap, whereas ChatGPT can be used continuously. Some say “Claude is by far the best… [but] he’s a prude” in terms of content allowed (meaning it refuses certain topics like drug advice – OpenAI does too, but perhaps Claude’s manner stands out). Others remain partial to ChatGPT, particularly for tasks like factual QA, coding explanations, or when they need quick, correct answers without fluff. There are also mentions that Claude’s answers feel more original and less templated than ChatGPT’s, which can repeat certain phrases or structures. For example, Claude varies its wording and doesn’t start every answer with “Certainly!” or “As an AI language model…” – a quirk that earlier ChatGPT versions had but GPT-4 largely eliminated.

Integration and Ecosystem: ChatGPT, by virtue of OpenAI’s partnerships, is finding its way into many products (e.g., built-in to web browsers, office software, etc.). This means for real-world usage, GPT-4o is accessible in more contexts. Claude, meanwhile, has been integrated into fewer big-name consumer products but is directly accessible via API and through Anthropic’s own interfaces. One interesting real-world note: Claude can handle uploading and analyzing files (PDFs, etc.) directly in the Claude.ai chat, whereas ChatGPT’s web UI doesn’t allow file attachments (OpenAI’s approach was to handle file inputs via the Code Interpreter plugin or by copy-pasting text). This file analysis capability made Claude very popular for students and researchers – you could just give it a PDF link or attach a file for summary. ChatGPT-4o can certainly do similar analysis, but the user must paste the text or use workarounds if using the ChatGPT interface (ChatGPT Enterprise added a feature to upload multiple files, but that’s not in the regular Plus UI yet as of 2025).

Emerging Use Cases: Both models are now being used as agents (e.g., AutoGPT-style autonomous agents that plan and execute tasks). Claude 4’s tool-use features and focus on “AI agents” in its design suggest it may perform very well controlling other tools or in long autonomous runs. Indeed, Anthropic mentioned Opus 4 can work continuously for several hours and thousands of steps without losing focus. This is promising for agent applications (like AI assistants that manage your email or do research for you). GPT-4o can also be used in such scenarios (and many AutoGPT frameworks use GPT-4), but OpenAI hasn’t publicized specialized “agentic” optimizations beyond the generic model. Early adopters note that Claude is less likely to get stuck in loops when acting as an autonomous agent and can utilize its scratchpad memory effectively. Meanwhile, GPT-4o’s speed and API cost reductions make it a strong choice for real-time agent loops where response time matters.

Conclusion of UX: If you’re a user deciding between them: ChatGPT-4o might be your pick for slightly higher factual precision, integration with other apps and services, multi-modal convenience (if you want voice and image outputs), and unlimited usage on a higher plan. Claude 4 might be your pick if you value a more conversational partner that can digest huge contexts and produce very rich, nuanced responses (especially for writing, ideation, or analyzing long content). Many find Claude more “enjoyable” to chat with for non-factual, open-ended conversations, whereas ChatGPT is the workhorse for tasks that need accuracy and brevity. Both are continually improving, and user experiences will evolve as updates roll out. At this stage (late 2024–2025), having access to both and switching between them for different tasks is arguably the optimal strategy – they complement each other well.

Summary Table: ChatGPT-4o vs Claude 4

Below is a side-by-side summary comparing GPT-4 Omni and Claude 4 across the key dimensions:

Dimension	ChatGPT-4o (OpenAI GPT-4 “Omni”)	Claude 4 (Anthropic Claude Opus/Sonnet)
Reasoning Ability	Excellent logical reasoning; slightly edges Claude in some benchmarks (e.g. GPT-4o ~88.7 MMLU vs Claude ~87). No native tool-use loop, but very strong chain-of-thought internally.	Excellent complex reasoning, especially with new tool-use mode. Matches GPT-4-level on knowledge tests (Opus 4 ~87.4 MMLU). Extended thinking allows external searches/calculations to boost reasoning.
Creativity & Generation	Highly creative and versatile. Adapts to many styles/genres; can mimic slang or specific tones precisely. Tends toward concise, structured storytelling unless prompted for more. Strong multilingual creativity (50+ languages).	Very creative with a more human-like, empathetic tone. Tends to produce longer, vivid narratives by default. Excels at brainstorming and imaginative writing, often feeling more “personable” and expressive.
Coding & Dev Tasks	Top-tier coding skills (solves ~90% on HumanEval). Great at explaining code and debugging. Offers Code Interpreter plugin to actually run code. API cost 50% lower than before, so coding with GPT-4o is more affordable. Used in GitHub Copilot and many dev tools.	Arguably the best coding model as of 2025. Excels in large codebase understanding and multi-file edits. Leads on SWE-bench (72.5% solved). Can maintain long coding sessions (hours) reliably. New Claude Code integrations (VS Code, SDK) enable tight IDE feedback.
Writing & Summarization	Produces clear, coherent long-form text. Summaries are concise and factual. Can adjust tone when instructed, though default is straightforward. 128k context allows long inputs (e.g., can summarize big docs in parts). Strong at style imitation when given examples.	Produces flowing, comprehensive text with a natural tone. Excellent at summarizing very large texts in one go (200k context) while keeping nuance. Defaults to a friendly, detailed writing style. Adapts to instructions for tone/length well, often injecting empathy or flair as needed.
Factual Accuracy & Hallucinations	Very high factual accuracy; tends to refuse answering if unsure. OpenAI fine-tuning reduces hallucinations (one study: GPT-4 ~84% vs Claude ~64% on certain factual benchmark). Will cite sources when using browse plugins. Still can err on obscure queries, but generally cautious and correct.	Also very accurate, with improvements in groundedness. Often provides lots of detail (which can sometimes include minor inaccuracies if not monitored). Uses Constitutional AI to stay factual and safe. In practice, users find Claude’s answers usually reliable and comprehensive, though it may occasionally “fill in” details if it thinks it’s being helpful. Both models require verification for critical facts.
Speed & Latency	Fast – ~110 tokens/sec generation, ~320ms response in voice mode. Much faster than original GPT-4. Real-time feel in chat; streams answers smoothly. Higher API rate limits than before. ChatGPT can handle user interruptions and continue seamlessly.	Fast in instant mode – near-immediate replies for normal queries. Also supports an “extended” mode for complex tasks (slower due to deliberate thinking). Generally streams long answers quickly. Slightly lower throughput than GPT-4o in token/sec (GPT-4o outpaced Claude 3 in tests), but difference is minor for most users.
Context Window	128k tokens max (huge upgrade from 32k GPT-4). In practice, plus users typically had up to 32k; 128k is available via API and specific plans. Great for long conversations or documents (dozens of pages).	200k tokens – industry-leading context length. Can easily handle entire books or massive logs in one prompt. Ideal for tasks like analyzing lengthy contracts or multi-document summaries. Outperforms GPT-4o in ultra-long context retention.
Multimodal Features	True multimodal: Accepts text, images, audio, even video frames as input. Outputs text, can speak answers in human-like voices, and can generate images natively. Essentially an all-in-one model for vision, speech, and language. (Audio input/output on API is limited release; fully available in ChatGPT apps).	Mixed modality: Accepts text and images as inputs. No native audio or video input (voice input uses speech-to-text externally). Outputs text only (voice responses are text-to-speech in app). No built-in image generation. Focuses more on text-based multimodal (e.g. describing images). Recently added voice chat feature in apps to stay competitive, but underlying model is text-centric.
Cost (API)	Full GPT-4o ~ 50% cheaper than previous GPT-4 (approx $0.03/1K output tokens). GPT-4o mini is extremely cheap: $0.15 per million input tokens. Encourages high-volume use with lower costs. Fine-tuning supported for custom models. Azure and OpenAI API both offer GPT-4o.	Opus 4: $15 per million input, $75 per million output (~$0.075/1K out). Sonnet 4: $3 per million in, $15 per million out ($0.015/1K out, 5× cheaper than Opus). Pricing unchanged from Claude 2. Thus, Claude can be cheaper per call if using Sonnet, but Opus (for max performance) is costlier than GPT-4o. Both models available via API, AWS, GCP with same pricing.
Consumer Pricing	Free tier: GPT-4o mini available free in ChatGPT (limited msgs, falls back to 3.5 when limit hit). Plus $20/mo: Priority access to GPT-4o full model, faster response, plugins, GPT-4 vision/voice, ~5× higher message limits. Pro $200/mo: Essentially unlimited GPT-4o usage, 32k context access, highest priority. Enterprise plans for orgs (custom pricing, unlimited, privacy guarantees).	Free tier: Claude 4 Sonnet free to use with daily message cap (generous, but heavy use will hit limits). Pro ~$20/mo: Higher daily limits (5× free), priority access, includes Claude Opus 4 usage for complex queries. Max $100/mo: 5× Pro usage. Max $200/mo: 20× Pro usage (very high cap for power users). No truly unlimited plan yet (Anthropic may consider in future). Team and Enterprise plans offer more usage and features for businesses.
Benchmark Performance	Near or at state-of-the-art on all major benchmarks. Wins in many standard tests: e.g. highest on 4 of 6 OpenAI benchmarks (MMLU, Code, etc.). Averages ~65% win rate on human pairwise comparisons (Chatbot Arena) post-GPT-4o. Essentially defined the “GPT-4-class” standard that others compare to.	Equally strong on most benchmarks by latest generation. Slightly lagged original GPT-4 on some academic tests (Claude 3: 79% vs GPT-4 86% MMLU), but Claude 4 now at parity (85–87% MMLU). Excels in coding benchmarks (outscoring GPT-4 on SWE/Terminal tasks). Took #1 on Chatbot Arena in early 2024, and Claude 4 is considered on par with or better than GPT-4-class by many real-world evaluations.
User Experience & Use Cases	Polished and controlled. Great for factual Q&A, programming help, summarization, and as a productivity tool. Tone is neutral-professional unless customized. Integrates with plugins (web browsing, etc.) making it versatile for tasks like travel booking, math, or research with citations. Vast adoption in products (Bing, Office, etc.). Free users get strong service; Plus/Pro for heavy use or advanced features. Some may find it less “chatty” or personable, but very efficient and reliable.	Engaging and insightful assistant. Fantastic for deep dives into long documents, creative brainstorming, and supportive conversation. Tone is friendly and empathetic, which users love for advice or emotional support scenarios. Tends to produce very comprehensive answers, which can be a pro or con depending on the need. Less integrated into third-party services, but available on multiple platforms (web, mobile, Poe). Power users adore its capability, calling it “the best in almost every way except limits”. Ideal for those who want a “collaborator” feel.

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