DeepSeek All Models Available: families, capabilities, and deployment options

DeepSeek has evolved from a single open-weight model into a complete ecosystem of general, reasoning, and specialist models, each optimized for different applications such as chat, coding, mathematics, and formal logic. As of late 2025, the company provides access to its models across web, app, API, and cloud environments, combining large-context architectures, open-weight transparency, and developer-focused APIs.

·····

.....

The DeepSeek V3 family and its current versions.

The V3 line is DeepSeek’s general-purpose foundation model family, designed for language understanding, multi-turn dialogue, and tool use. It has evolved through several refinements, each expanding the model’s context length, reasoning ability, and performance efficiency.

• DeepSeek-V3 (2024–2025): The original large dense model trained on approximately 14.8 trillion tokens, released with open weights. It was the company’s first model capable of full-context chat, creative writing, and data summarization.

• DeepSeek-V3.1 (2025): A refinement trained on an additional 840 billion tokens, adding extended context capacity and a new tokenizer optimized for multilingual comprehension.

• DeepSeek-V3.1-Terminus: A stabilization update improving agentic consistency, error handling, and tool-calling reliability.

• DeepSeek-V3.2-Exp: The current flagship, incorporating Sparse Attention for greater efficiency in long-context reasoning. This version powers both the chat and reasoner endpoints in the official API and is live across the web and app platforms.

The V3.2-Exp model is positioned as the standard engine for both everyday chat and professional workflows. It supports 128,000-token context windows, enabling analysis of long documents or datasets within a single session.

·····

.....

The DeepSeek R1 reasoning models.

The R1 family represents DeepSeek’s line of models specialized in structured reasoning, reflection, and step-by-step problem solving. Unlike the general V3 models, the R1 series is optimized for logic-intensive and analytical workloads.

• DeepSeek-R1-Zero: The first reasoning baseline trained using reinforcement learning on reasoning traces.

• DeepSeek-R1: The initial reasoning-tuned model, incorporating improved chain-of-thought consistency and better factual recall.

• DeepSeek-R1-0528: A major 2025 release that further enhances multi-step logical decomposition and mathematical reasoning accuracy.

These models provide the foundation for the deepseek-reasoner endpoint in the API, which exposes reasoning behavior through a “thinking” mode. This mode maintains a reflection phase before final response generation, improving the accuracy of complex analyses, code interpretation, and academic-style answers.

·····

.....

Specialist models for coding, mathematics, and proofs.

Beyond its general and reasoning models, DeepSeek maintains a portfolio of specialized open-weight systems that target domain-specific applications.

• DeepSeek-Coder (v1 & v1.5): A code-focused model line trained on multi-language repositories, optimized for code completion, refactoring, and documentation.

• DeepSeek-Coder-V2 (MoE): A mixture-of-experts code model trained on over six trillion tokens, offering repository-level reasoning and context lengths up to 16,000 tokens.

• DeepSeek-Math (7B): A compact yet highly accurate model fine-tuned on mathematical datasets, particularly effective in symbolic reasoning and high-school-level problem solving.

• DeepSeek-Prover-V2 (671B): A formal theorem-proving model built on Lean 4 frameworks, capable of generating and verifying logical proofs with extended token handling (over 160,000 context tokens).

Each specialist model is available as open weights on public repositories, supporting integration into local environments, research pipelines, or fine-tuning workflows.

·····

.....

Available models in the API and developer ecosystem.

In the DeepSeek API, there are currently two main endpoints:

1. deepseek-chat — The default chat interface using V3.2-Exp for conversation, summarization, and creative writing.

2. deepseek-reasoner — A reflective reasoning endpoint that uses the same model with internal thinking passes for analytical depth.

Both support 128K context windows, with 32K–64K output token capacities, and share tool-calling functionality for external actions such as data retrieval or code execution. Developers can continue to access V3.1-Terminus for compatibility testing or benchmarking, though V3.2-Exp is now the standard release.

API users can send multimodal text, structured instructions, or tool calls, making the platform adaptable for chatbots, analytical agents, and document processing systems.

·····

.....

Table — DeepSeek model families and their uses.

Model Family	Main Versions	Primary Use Case	Context Limit	Availability
V3 Line	V3, V3.1, V3.1-Terminus, V3.2-Exp	General chat, summarization, reasoning, tool use	128K tokens	API, web, app, open weights
R1 Line	R1-Zero, R1, R1-0528	Deep reasoning, multi-step logic, analysis	128K tokens	API (reasoner endpoint), open weights
Coder Line	Coder v1, v1.5, V2 (MoE)	Coding, code generation, repository-level reasoning	16K tokens	Open weights
Math Model	DeepSeek-Math (7B)	Symbolic reasoning, numerical problem solving	32K tokens	Open weights
Prover Model	DeepSeek-Prover-V2	Formal theorem proving, logic validation	160K tokens	Open weights

This table highlights how DeepSeek’s suite of models covers both general-purpose and specialized reasoning scenarios.

·····

.....

Cloud, app, and open-weight availability.

DeepSeek models are accessible through multiple environments depending on user type and technical need:

• App and Web Access: The DeepSeek website and mobile app provide free usage of DeepSeek-V3.2, with integrated reasoning capabilities and long-context chat sessions.

• API Integration: Developers can connect via the DeepSeek API using deepseek-chat or deepseek-reasoner. Both share unified pricing, scaling, and rate limits.

• Cloud Deployment: DeepSeek-V3.1 is integrated into Amazon Bedrock, while reasoning models such as R1 are listed in partner cloud ecosystems.

• Open Weights: Research and community versions of all major models (V3, R1, Coder, Math, Prover) are distributed on platforms like Hugging Face and GitHub.

This modular availability allows DeepSeek to serve individual users, enterprise deployments, and open research simultaneously.

·····

.....

Release timeline and model evolution.

DeepSeek’s roadmap has been characterized by rapid iteration and continuous open releases:

• December 2024: DeepSeek-V3 base model released with open weights.

• January 2025: Launch of DeepSeek-R1 and R1-Zero reasoning models.

• April 2025: Release of DeepSeek-Prover-V2 and math-specialist updates.

• August 2025: Launch of DeepSeek-V3.1 and the subsequent Terminus refinement.

• September 2025: Introduction of DeepSeek-V3.2-Exp featuring Sparse Attention, optimized throughput, and expanded context window.

Each release has improved reasoning coherence, multilingual handling, and efficiency, while maintaining open publication for reproducibility and external adoption.

·····

.....

Operational recommendations.

• For everyday users: Use the web or app interface running V3.2-Exp for research, writing, and document summarization.

• For developers: Integrate via the API and select between deepseek-chat (fastest) or deepseek-reasoner (reflective) depending on task complexity.

• For research and fine-tuning: Download open-weight models such as V3.1, R1, or Coder-V2 to build domain-specific assistants.

• For code and math: Use the dedicated Coder or Math models, which outperform general chat models in narrow technical tasks.

These configurations allow users to balance reasoning depth, cost efficiency, and performance according to their workloads.

·····

.....

Summary of DeepSeek’s model ecosystem.

The DeepSeek ecosystem now spans six main model families—V3, R1, Coder, Math, Prover, and Reasoner—covering general intelligence, specialized reasoning, and open-weight research. The V3.2-Exp model anchors all major deployments, providing high performance and a 128K context window for chat and analytical work. The R1 line continues to define DeepSeek’s reasoning standard, while the Coder, Math, and Prover models reinforce its technical specialization.

With unified access through web, app, API, and open repositories, DeepSeek has become one of the most diversified AI platforms of 2025, combining commercial usability with full open-weight transparency.

.....

FOLLOW US FOR MORE.

DATA STUDIOS

.....[datastudios.org]