ChatGPT 5.4 Pro vs Claude Opus 4.6 vs Gemini 3 Pro: Full Report and Comparison on Pricing, Access, Context Window, Multimodality, and what actually changes across app and API

These three names sit at the top end of their respective ecosystems, but they do not line up as neatly as many comparison pages suggest.

GPT-5.4 Pro is the easiest one to classify, because OpenAI exposes it both as a high-end ChatGPT mode and as a clearly named API model.

Claude Opus 4.6 is similarly straightforward, because Anthropic presents it as a flagship Claude model across claude.ai, the API, and major cloud platforms.

Gemini 3 Pro is the least cleanly aligned of the three, because Google uses Gemini 3 Pro in the consumer app layer while the developer-facing documentation is more explicit around Gemini 3.1 Pro Preview.

That naming split is not a minor editorial issue.

It changes what is really being compared when someone moves from app usage to API pricing or Vertex deployment.

The most useful way to compare these models is therefore not through vague claims about which one is smartest.

The more serious comparison starts with product layer, access path, cost structure, context limits, multimodality, and the constraints each vendor places around the highest-end experience.

This is also where the differences become commercially meaningful.

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Understand what is actually being compared.

These three offerings overlap in role, but they are not exposed by their vendors in exactly the same way.

GPT-5.4 Pro is OpenAI’s highest-capability GPT-5.4 option for the hardest tasks and long-running workflows in ChatGPT, and it is also exposed as gpt-5.4-pro in the API.

Claude Opus 4.6 is Anthropic’s flagship Claude model and is available on claude.ai, in the API, and on major cloud platforms.

Gemini 3 Pro is a real app-facing Google label, but the developer-facing materials more concretely document Gemini 3.1 Pro Preview as the API and Vertex object.

That means the OpenAI and Anthropic sides are easier to compare directly, because the same model family is more visibly continuous between app and API.

Google’s side is real, but it is less naming-stable between consumer and developer surfaces.

This matters before any discussion of quality.

If the compared object is not the same kind of object across vendors, the whole comparison can become distorted.

OpenAI and Anthropic are more clearly exposing named flagship models across both app and API.

Google is exposing a flagship family with a more visible split between what the consumer sees and what the developer docs specify.

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· GPT-5.4 Pro is a clearly named app and API object.

· Claude Opus 4.6 is also a clearly named app and API object.

· Gemini 3 Pro is real, but Google’s developer-side documentation is more explicit around Gemini 3.1 Pro Preview.

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Product-layer alignment

Area	GPT-5.4 Pro	Claude Opus 4.6	Gemini 3 Pro / 3.1 Pro
App-facing flagship label	Yes	Yes	Yes
API-facing flagship label	Yes	Yes	Partly split
Naming continuity across app and API	High	High	Lower
Comparison cleanliness	High	High	More conditional

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See where each one is actually available.

The three models are all available across important surfaces, but the exact surface map is different.

GPT-5.4 Pro is available in ChatGPT and the OpenAI API, with OpenAI also indicating availability posture for Pro, Business, Enterprise, and Edu in ChatGPT contexts.

Claude Opus 4.6 is available on claude.ai, through the Anthropic API, and on major cloud platforms.

Gemini 3 Pro and its developer-side counterpart are available through the Gemini app, the Gemini API, Google AI Studio, Vertex AI, and NotebookLM in Google’s official materials.

OpenAI’s surface posture is the most tightly controlled at the top end.

Anthropic’s is broad and enterprise-friendly.

Google’s is broad as well, but the model naming and rollout language require more care when switching surfaces.

This becomes important in practical research and enterprise planning.

A model that is easy to identify in one surface but ambiguous in another creates friction for procurement, engineering, and editorial comparison.

That is why the Gemini side needs more explanation than the other two even before performance is discussed.

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· GPT-5.4 Pro is confirmed in ChatGPT and the OpenAI API.

· Claude Opus 4.6 is confirmed in claude.ai, the API, and major cloud platforms.

· Gemini 3 Pro is app-visible, while the API and cloud surfaces are more explicitly documented as Gemini 3.1 Pro Preview.

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Availability surfaces

Surface	GPT-5.4 Pro	Claude Opus 4.6	Gemini 3 Pro / 3.1 Pro
Main app	ChatGPT	claude.ai	Gemini app
Direct API	Yes	Yes	Yes
AI studio / developer studio	OpenAI platform	Anthropic Console/API	Google AI Studio
Cloud platform route	Not the main public framing	Yes	Yes via Vertex AI
Broader knowledge product tie-in	Limited in compared sources	Limited in compared sources	Yes via NotebookLM

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Learn how the API pricing changes the comparison immediately.

The biggest hard difference across the three models is price.

On OpenAI’s current developer pricing, GPT-5.4 Pro costs $30 per 1 million input tokens and $180 per 1 million output tokens for short-context standard pricing, with higher pricing for long-context sessions above the threshold.

Anthropic prices Claude Opus 4.6 at $5 per 1 million input tokens and $25 per 1 million output tokens, with batch and caching-related mechanisms also documented in the broader Anthropic pricing structure.

Google prices Gemini 3.1 Pro Preview at $2 per 1 million input tokens and $12 per 1 million output tokens up to 200k tokens, then $4 input and $18 output above that threshold.

That makes GPT-5.4 Pro by far the most expensive of the three on direct list pricing.

Claude Opus 4.6 is materially cheaper than GPT-5.4 Pro but still much more expensive than Gemini on direct token cost.

Gemini is the lowest-cost option of the three on the published developer schedule reviewed here.

This is not a minor pricing gap.

It is a structural difference that changes who can justify these models in production.

The cheapest model in this comparison is not only cheaper by a margin.

It is cheaper by a factor large enough to change workload design, experimentation freedom, and deployment economics.

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· GPT-5.4 Pro is the most expensive model in the comparison on published API pricing.

· Claude Opus 4.6 is the middle-priced option.

· Gemini 3.1 Pro Preview is the cheapest on current published developer pricing.

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API list pricing

Model	Input price	Output price	Pricing structure note
GPT-5.4 Pro	$30 / 1M	$180 / 1M	Higher long-context pricing beyond threshold
Claude Opus 4.6	$5 / 1M	$25 / 1M	Mid-tier flagship pricing
Gemini 3.1 Pro Preview	$2 / 1M up to 200k, $4 above	$12 / 1M up to 200k, $18 above	Threshold-based split

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Understand why the cost comparison is still more complicated than it looks.

The published API numbers are clear, but the real cost story depends on where the model is being consumed.

OpenAI separates ChatGPT plan access from API pricing much more sharply than many casual comparisons admit.

A ChatGPT user evaluating GPT-5.4 Pro is not experiencing the same commercial object as an API team buying gpt-5.4-pro by the token.

Those are related products, but they are not the same billing layer.

Anthropic is similar in the sense that claude.ai access and API usage are connected but not identical in cost logic.

Claude Pro, Max, Team, and Enterprise access live inside a broader Claude product structure, while API pricing is a separate developer layer.

Google has the same app-versus-developer split, but with an extra naming complication.

A user in the Gemini app may be thinking in terms of Gemini 3 Pro access and plan limits, while a developer may be budgeting around Gemini 3.1 Pro Preview token pricing.

So the direct API table is essential, but it is not the whole story.

The real commercial comparison depends on whether the question is app access, API deployment, cloud deployment, or some combination of all three.

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Check the consumer-plan and premium-access structure.

At the app level, all three vendors put their highest-end capability behind some form of paid or higher-tier access, but the shape of that access differs.

OpenAI’s materials position GPT-5.4 Pro as a higher-end ChatGPT option associated with upper-tier access rather than a free or broadly standard mode.

Anthropic’s pricing places Claude Pro at around the $20-per-month level and Max at a much higher starting tier, while confirming that Opus 4.6 is available in claude.ai.

Google’s subscription and release-note materials show Google AI Pro at $19.99 per month and tie stronger access to Gemini 3.1 Pro to paid plans, while also describing Gemini 3 Pro as rolling out broadly in the app with tighter limits at lower tiers.

This means the premium-app experience is not uniform.

OpenAI is the most clearly restrictive in how it presents the top mode.

Anthropic packages high-end access inside a broader Claude subscription ecosystem.

Google packages high-end Gemini access inside a plan system that is more app-integrated and more visibly tier-sensitive on prompt limits.

That difference affects user expectations.

A user coming from ChatGPT Pro is dealing with a highly capability-focused but more constrained mode.

A user coming from claude.ai is dealing with a flagship model inside a more unified Claude environment.

A user coming from the Gemini app is dealing with a more app-integrated and multimodal plan structure with wider consumer-facing rollout language.

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· The top-end app experience is paid or higher-tier across all three vendors.

· OpenAI’s top mode is the most overtly gated and specialized.

· Anthropic’s is packaged inside a broader Claude subscription structure.

· Google’s is tied to app rollout and paid-plan limit expansion.

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Consumer and premium access posture

Area	GPT-5.4 Pro	Claude Opus 4.6	Gemini 3 Pro / 3.1 Pro
High-end app access exists	Yes	Yes	Yes
Clear low-tier availability	No	Broader Claude access exists, exact model path depends on plan	Basic access exists with stronger paid limits
Premium plan relevance	High	High	High
Plan structure simplicity	Moderate	Moderate	Lower due to app/API naming split

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See how the context window changes the technical reading.

All three models are long-context models, but their exact numbers and pricing implications differ.

GPT-5.4 Pro has a 1.05 million token context window in the API, with long-context pricing applying beyond 272k input tokens.

Claude Opus 4.6 has a 1 million token context window and 128k maximum output tokens in Anthropic’s current documentation.

Gemini 3.1 Pro Preview has a 1 million token input context and 64k output in Google’s developer docs.

So the headline input context is broadly similar across the three.

The more interesting differences sit in output ceilings, price thresholds, and what each vendor does around that context in practice.

OpenAI gives the largest input number of the three in this set, but also ties that high ceiling to the most aggressive cost structure.

Anthropic is slightly smaller on input context but stronger on maximum output than Google in the compared documentation.

Google is competitive on input context but more conservative on output ceiling in the current developer-facing materials.

For large reports, legal bundles, technical repositories, and other heavy-input tasks, all three qualify as serious long-context systems.

The decision point is less about whether they are large-context models and more about how much that context costs, how much output can be returned, and how the model is meant to be used around that envelope.

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· All three models support around one million tokens of input context in the reviewed official material.

· OpenAI gives the highest input figure.

· Anthropic documents the highest output ceiling among the three here.

· Google’s output ceiling is lower in the current developer documentation.

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Context and output posture

Model	Input context	Output ceiling	Important note
GPT-5.4 Pro	1.05M	Not the lead headline in compared source set	Long-context pricing threshold above 272k input
Claude Opus 4.6	1M	128k	Strong output ceiling
Gemini 3.1 Pro Preview	1M	64k	Lower output ceiling than Anthropic in reviewed docs

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Learn how multimodality changes the product fit.

The three models are not equally shaped around multimodality.

GPT-5.4 Pro’s API page supports text output with text and image input, and it does not support audio or video in the compared API documentation.

Claude Opus 4.6 is part of Anthropic’s broader Claude environment, but the reviewed comparison materials here do not frame it as aggressively around app-level multimodal breadth as Google does for Gemini.

Google explicitly positions Gemini 3 Pro as strong for multimodal reasoning across text, images, audio, and video, especially in the app-facing materials and broader model-family framing.

This creates one of the clearest product-fit differences.

GPT-5.4 Pro is the most obviously reasoning-maximized and API-expensive option in the set, but it is not the broadest multimodal object in the reviewed materials.

Gemini is the most overtly multimodal and app-integrated of the three in the consumer-facing framing.

Claude sits in between, with strong flagship posture but without Google’s level of app-facing multimodal emphasis in the compared source set.

That matters for buyer intent.

A team buying for structured reasoning and high-precision difficult tasks may read this differently from a team buying for multimodal intake across media types.

A user choosing inside the app may also care less about raw model elegance and more about whether the product easily handles mixed-format work.

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Understand the feature-boundary differences inside the app.

OpenAI’s top mode is the most visibly capability-focused and tool-restricted in the compared app-layer documentation.

OpenAI explicitly says that Apps, Memory, Canvas, and image generation are not available with GPT-5.4 Pro inside ChatGPT.

That is an unusually sharp feature boundary for a flagship premium mode.

It tells you that OpenAI is treating GPT-5.4 Pro as a concentrated top-capability path rather than as the broadest all-tools ChatGPT environment.

Anthropic’s Opus 4.6 is not framed that way in the compared sources.

It appears more naturally inside the broader Claude app and subscription system rather than as a stripped specialist mode with a long list of missing app features.

Google’s Gemini 3 Pro posture is the opposite of the OpenAI one in tone.

It is tied more directly to app experience, multimodal usage, and Google AI plan integration rather than to a sharply reduced product envelope around the top model.

This is one of the clearest practical differences in the article.

If the question is which one feels most like a pure high-end reasoning mode with less in-app convenience, the answer is GPT-5.4 Pro.

If the question is which one feels most integrated into a broad app-centric multimodal environment, the answer points more toward Gemini.

Claude Opus 4.6 is the most balanced of the three in how the current reviewed sources present its place inside the app layer.

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· GPT-5.4 Pro has the sharpest in-app feature restrictions in the reviewed comparison.

· Claude Opus 4.6 is presented more as a flagship inside a unified Claude environment.

· Gemini 3 Pro is the most app-integrated and multimodal in the consumer-facing framing.

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App-layer feature posture

Area	GPT-5.4 Pro	Claude Opus 4.6	Gemini 3 Pro
Top-capability specialist mode	Strongly yes	Less sharply framed that way	Less sharply framed that way
Explicit missing app features in compared sources	Yes	Not emphasized that way	Not emphasized that way
Strong app integration emphasis	Limited in compared sources	Moderate	Strong

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See what the Gemini naming split does to the whole comparison.

Gemini is the model family that creates the most editorial and technical friction in this comparison.

The issue is not that Gemini 3 Pro is unreal.

The issue is that the consumer-facing and developer-facing names do not line up as cleanly as OpenAI’s and Anthropic’s do in the official materials reviewed here.

In the app, Gemini 3 Pro is a visible user-facing object.

In the API and Vertex context, Gemini 3.1 Pro Preview is the most concretely documented developer object.

That means anyone writing a serious comparison has to decide whether they are comparing app experience, API economics, or both.

This is not just a naming nuisance.

It affects every downstream comparison table.

Pricing changes.

Rollout language changes.

Even the exact model that is being measured changes if the writer is careless.

That is why the Google side is the one that most often gets oversimplified.

A short comparison can hide the split.

A complete one has to name it and keep it visible all the way through.

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Check what is actually most comparable across the three.

The safest apples-to-apples comparison here is not benchmark supremacy.

The strongest grounded comparison is on product role, availability surface, API pricing, context window, output ceiling, multimodality posture, and app-level feature boundaries.

That is where the sources are strongest and the differences are real.

All three vendors say their top models are meant for hard reasoning, coding, and difficult tasks.

That is useful, but it does not settle a universal winner.

The practical comparison is much clearer than the marketing comparison.

OpenAI gives the most expensive and most capability-concentrated top mode.

Anthropic gives a flagship model with broad app, API, and cloud presence at a mid-tier price point.

Google gives the cheapest direct developer price and the strongest overt multimodal app posture, but with the most naming and rollout complexity.

That is already enough to support a very strong article.

It just does not support a serious claim that one model is simply the best for every user, every team, and every deployment context.

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Know which one fits which kind of user best.

GPT-5.4 Pro fits the user or team that is willing to pay the highest price for a highly concentrated top-capability route.

That is the cleanest reading of OpenAI’s positioning and cost structure.

The trade-off is obvious.

The model is expensive, and the app mode is more restricted than many premium users might expect, but the product is clearly being aimed at the hardest tasks and long-running workflows.

Claude Opus 4.6 fits the user or team that wants a high-end flagship model with broad availability across app, API, and cloud, without stepping into OpenAI’s extreme pricing band.

It is expensive enough to remain a premium model, but much easier to justify economically than GPT-5.4 Pro in direct API deployment.

Gemini 3 Pro or Gemini 3.1 Pro fits the user or team that prioritizes lower direct API cost, stronger overt multimodality, and Google’s broader app-and-cloud ecosystem, while accepting more naming and rollout complexity.

That is the strongest stable reading of Google’s side in this comparison.

The decision therefore depends less on vague intelligence rankings and more on what the buyer is actually optimizing for.

If the priority is maximum top-end capability posture and price is secondary, GPT-5.4 Pro is the cleanest fit.

If the priority is flagship quality with broader deployment continuity and saner direct pricing, Claude Opus 4.6 is easier to defend.

If the priority is multimodal breadth and cheaper developer economics inside Google’s ecosystem, Gemini 3 Pro or 3.1 Pro becomes the strongest commercial candidate.

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