DeepSeek V4 Pro: the flagship V4 model
Overview
DeepSeek V4 Pro: 1.6T total parameters, 49B active, 1M token context
Pro is the flagship variant of the DeepSeek V4 series. With 1.6T total parameters and 49B activated per token, it delivers the highest level of reasoning and precision in the V4 family, while maintaining a one-million-token context window. Available on OpenRouter at $1.74 / 1M input tokens and $3.48 / 1M output tokens.
Pro Architecture
1.6T total parameters, 49B activated per inference
Pro uses DeepSeek's MoE (Mixture of Experts) architecture with hybrid attention, variety-constrained hyper-connections, and the Muon optimizer. With 49B parameters activated per token — versus 13B for Flash — Pro delivers significantly deeper reasoning for complex tasks.
Ideal for advanced reasoning, complex code, mathematics, and agentic workflows.
1M token context
One-million-token context window for long tasks
Pro supports a one-million-token context window, enabling processing of entire codebases, long legal documents, or multi-step analyses in a single session. Hybrid attention and architectural optimizations maintain coherence across the full context.
Use Pro for tasks that require both deep reasoning and long context.
Model choice
Pro vs Flash
Pro: 1.6T total / 49B active. Flash: 284B total / 13B active. Same 1M token context.
Pro is reserved for unlimited plans and tasks requiring more depth. Flash is the default free entry point.
Technical
MoE Architecture
Mixture of Experts with hybrid attention, variety-constrained hyper-connections, and Muon optimizer.
The MoE architecture activates only a fraction of parameters per token. Pro activates 49B parameters, giving it superior reasoning capacity over Flash (13B active).
Usage
Reasoning modes
Non-think, Think High, and Think Max to adjust analysis depth.
Non-think prioritizes speed. Think High improves precision. Think Max pushes reasoning to the maximum, recommended with at least 384K tokens of context.
Evaluation
Benchmarks
MMLU-Pro, HumanEval, GSM8K, LongBench-V2, LiveCodeBench, SWE Verified, MCPAtlas.
Official tables cover general knowledge, reasoning, code, math, long context, and agentic tasks. Pro outperforms Flash on complex tasks.
Integration
OpenAI-compatible API
API identifier: deepseek-v4-pro. Compatible with OpenAI and Anthropic format.
Use deepseek-v4-pro in your existing API integrations. Recommended temperature: 1.0, top_p: 1.0.
Deployment
Open weights
Weights available on Hugging Face for local or cloud deployment.
Pro can be run locally. The model card includes encoding instructions, sampling settings, and compatibility notes. FP8 supported.
Why Pro
Pro is built for reasoning depth and complex tasks
With 49B active parameters and 1M token context, Pro offers the best balance of reasoning power and processing capacity for demanding tasks.
Advanced reasoning
49B parameters activated per token. Pro is positioned for complex analytical tasks, mathematical proofs, and multi-step reasoning.
Code and agents
Evaluated on LiveCodeBench, SWE Verified, Toolathlon, and MCPAtlas. Pro excels at complex developer workflows and agentic tasks.
Adjustable reasoning modes
Non-think for maximum speed, Think High for more precision, Think Max for the most difficult tasks.
Optimized long context
1M token context with hybrid attention. Process entire codebases or long documents in a single session.
Resources
Official DeepSeek V4 Pro links
Access weights, source code, and official documentation to deploy or evaluate Pro.
Weights and model card
- Official model card with benchmarks and deployment instructions.
- Weights available for local and cloud inference.
- FP8 instructions, encoding, and recommended sampling parameters.
Source code
- GitHub repository with integration examples and scripts.
- Compatible with standard inference frameworks.
- Documented prompt examples and use cases.
Recommended usage
- Temperature 1.0, top_p 1.0 for local deployment.
- Minimum 384K token context for Think Max.
- Test Pro on your complex workflows before choosing between Pro and Flash.
Official data
DeepSeek V4 Pro benchmarks: what the numbers say
The official model card publishes results on knowledge, reasoning, code, math, long context, and agentic tasks. Here are the key points.
Compare Pro and Flash on benchmarks that match your real use cases, not just general leaderboards.
Pro: 1.6T total parameters, 49B activated. Flash: 284B total parameters, 13B activated. Same 1M token context.
Benchmarks covered: MMLU-Pro, HumanEval, GSM8K, LongBench-V2, LiveCodeBench, SWE Verified, Toolathlon, MCPAtlas.
Pro activates 49B parameters per token — nearly 4x more than Flash (13B) — for deeper reasoning.
Instruct modes: Non-think (speed), Think High (precision), Think Max (maximum reasoning, min. 384K tokens).
Advanced reasoning
Pro for tasks that require in-depth analysis
With 49B active parameters, Pro is the natural choice for complex analyses, mathematical proofs, legal reasoning, and multi-step agentic workflows.
- Complex document analysis, financial reports, long contracts.
- Advanced mathematical reasoning and structured problem solving.
- Agentic workflows requiring multiple reasoning steps.
Code and development
Pro for complex development tasks
Pro excels on code benchmarks like LiveCodeBench and SWE Verified. Use it for code review, refactoring large codebases, and development tasks that require deep context understanding.
- Review and refactoring of large codebases.
- Test generation and complex debugging.
- Agentic workflows for development automation.
Local deployment
Deploy Pro locally or via API
Pro's open weights are available on Hugging Face. The model card includes encoding instructions, recommended sampling parameters, and compatibility notes.
- Weights available on HuggingFace for local deployment.
- FP8 supported to reduce memory footprint.
- Compatible with standard inference frameworks.
FAQ
DeepSeek V4 Pro: basics and architecture
Answers to the most common questions about the Pro model.
Pro is the flagship variant of the DeepSeek V4 series. 1.6T total parameters, 49B activated per token, 1M token context. It is the most powerful model in the V4 family.
Pro: 1.6T total parameters, 49B active. Flash: 284B total, 13B active. Both have 1M token context. Pro is more powerful, Flash is faster and cheaper.
MoE (Mixture of Experts) with hybrid attention, variety-constrained hyper-connections, and Muon optimizer. Same architectural family as Flash, but with more active parameters.
Yes, weights are available on Hugging Face. Check the license on the official model card.
FAQ
Performance and reasoning modes
What benchmarks and instruct modes mean in practice.
MMLU-Pro, HumanEval, GSM8K, LongBench-V2, LiveCodeBench, SWE Verified, Toolathlon, MCPAtlas. Cover knowledge, code, math, long context, and agents.
Non-think: fast response without extended reasoning. Think High: more precision. Think Max: maximum reasoning, requires at least 384K tokens of context.
Yes. Pro supports 1M token context with hybrid attention to maintain coherence across the full context.
Choose Pro for complex tasks: advanced reasoning, difficult code, math, agentic workflows. Flash is sufficient for everyday tasks and quick summaries.
FAQ
Deployment, API, and resources
How to use Pro in production or locally.
API identifier: deepseek-v4-pro. Compatible with OpenAI and Anthropic format. Available on OpenRouter at $1.74 / 1M input tokens.
Temperature 1.0, top_p 1.0 for local deployment according to the official model card.
Weights are available on Hugging Face. FP8 supported to reduce memory footprint.
The GitHub repository contains integration scripts, prompt examples, and technical documentation.
Resources
Everything you need to know about DeepSeek V4 Pro
Architecture, benchmarks, reasoning modes, API, local deployment, and comparison with Flash.
Get started
Test DeepSeek V4 Pro on a real task
Start with a complex analysis, code review, or long document. Compare Pro and Flash on the same workflow to choose the right model.