AI model by DeepSeek
DeepSeek V4 Pro for business
DeepSeek's model for demanding reasoning and agent work, with thinking effort levels, tool calling, JSON output and a 1 million token window.
- Reasoning
- Open weights
- Coding
- Open weights
- Reviewed on September 24, 2026
- DeepSeek
Capability tiersRelative, not benchmarks
Key facts about DeepSeek V4 Pro
- Model ID at review
- deepseek-v4-pro
- Provider
- DeepSeek
- Main category
- Reasoning
- Open weights
- Yes
- Last reviewed
- September 24, 2026
Fit
Where it fits and where it does not
Good at
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Demanding reasoning at a lower price than many frontier models.
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Thinking effort levels: low, high and max.
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Tool calling and JSON output for agents.
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Very long inputs, up to 1 million tokens.
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Coding and analysis.
Not the right choice for
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Image input, which it does not accept.
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Teams whose data rules exclude the hosted API.
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Simple tasks, where Flash is cheaper.
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Adoption without checking the license of the weights.
Use cases
Business use cases we would use it for
Analysis
Code tasks
Our notes
When we would choose it
DeepSeek V4 Pro is DeepSeek's model for demanding reasoning and agent workloads. It was updated in August 2026. It supports tool calling and JSON output, offers thinking effort levels of low, high and max, and has a 1 million token context window. It does not accept images.
Its price is well above DeepSeek's own Flash model but still low compared with many frontier reasoning models. That makes it interesting for agent work with many steps, where the cost of each task adds up quickly.
Open weights for V4 Pro are published, but we could not verify the license name at review time. Check it before you plan to host the model yourself.
As with all DeepSeek models, the key business question is data. Where the hosted API meets your rules, V4 Pro is a strong low-cost candidate for reasoning steps. Where it does not, self-hosting or a trusted host is the route, with the hardware cost that brings.
We would compare it with Claude Opus, GPT-6 Sol and Gemini Pro on your hardest real tasks, and look at cost per completed task rather than cost per request. See reasoning models.
Before you commit
Things to check before you commit
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Data location
Check where the hosted API processes data.
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License
Open weights are published. We did not verify the license name at review time.
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Effort levels
Tune thinking effort to balance quality, speed and cost.
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No vision
Use another model for images and scans.
Alternatives
Models to compare it with
DeepSeek V4.1 Flash
DeepSeek's default, best-value model: open weights under MIT, image input, tool calling, JSON output, optional thinking and a 1 million token window.
Claude Opus 5.5
Anthropic's recommended starting point for most serious work: long-running agentic coding and knowledge work, with a 1M token context window.
Qwen3.8-Max
Alibaba's current Qwen flagship for long autonomous coding and professional work, with image and video input, tool calling, JSON Schema output and a 1 million token window.
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Solutions, services and guides
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- Tool calling Tool calling is when an AI model asks the application to run a tool, such as a search or database lookup, and then uses the result in its answer.
FAQ
Questions people ask us
Have a question that is not here? Ask us directly.
No. For images, use DeepSeek V4.1 Flash or another multimodal model.
Settings that control how much the model reasons before answering: low, high and max.
R1 is no longer a separate current API model. Reasoning is now a mode of the V4 models.