DeepSeek V4 Pro
DeepSeek's flagship 1.6T parameter Mixture-of-Experts model, delivering frontier-class coding, math, and agentic reasoning with an ultra-efficient 1M context window.
Overview
What is DeepSeek V4 Pro
DeepSeek V4 Pro is a flagship 1.6-trillion parameter Mixture-of-Experts (MoE) open-weight model released in April 2026. It features 49 billion active parameters, a massive 1-million-token context window, and an advanced hybrid attention architecture. It delivers world-class reasoning, agentic coding, and deep world knowledge, rivaling top closed-source models.
Running it privately on Venice
On Venice, you can access DeepSeek V4 Pro under our anonymized privacy tier, ensuring your prompts are forwarded without storing your personal history. While served via a third-party provider that may retain prompt data per their policies, Venice acts as a protective buffer by stripping your identity. This lets you leverage its massive 1M context and agentic reasoning without direct Big Tech surveillance.
Assessment
Strengths and limitations
- State-of-the-art agentic coding capabilities, seamlessly integrating with AI agents like Claude Code and OpenClaw.
- Ultra-efficient Hybrid Attention (CSA + HCA) reducing KV cache to 10% and inference FLOPs to 27% compared to previous generations.
- Massive 1-million-token context window supported natively, ideal for digesting entire codebases or long documents.
- Excellent reasoning, math, and STEM capabilities, rivaling top-tier proprietary models.
- MIT license allows complete sovereignty, enabling organizations to self-host and modify the weights freely.
- Not natively uncensored; retains built-in alignment and safety guardrails from the creator.
- Served via a third-party provider on Venice, meaning Venice forwards requests anonymized, but the endpoint provider may retain prompt data.
- Requires massive hardware infrastructure to self-host due to its 1.6T total parameter size.
Capabilities
What it supports
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
Specifications
Datasheet
- Maker
- DeepSeek
- Released
- April 24, 2026
- Architecture
- Mixture-of-Experts (MoE) with Hybrid Attention (CSA + HCA)
- Parameters
- 1.6 Trillion total (49 Billion active)
- License
- MIT (Open Weights)
- Context window
- 1,000K tokens
- Max output
- 32.768K tokens
- Capabilities
- Function calling, Reasoning, Web search, Code-optimized
- Privacy on Venice
- Anonymized — prompts not stored
- Available on Venice since
- Apr 2026
API
Call it from your code
Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v4-pro",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $1.73 per 1M input tokens and $3.80 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Best for | Context window | Open weights | Price (Venice) | Primary strength |
|---|---|---|---|---|---|
| DeepSeek V4 Pro | The open-weight leader in cost-effective long-context reasoning. | 1M tokens | Yes | $1.73 / $3.80 | Agentic coding & reasoning |
| Claude Sonnet 4.6 | Proprietary benchmark leader, but significantly more expensive. | 1M tokens | No | $3.60 / $18 | Software engineering & general intelligence |
| DeepSeek V3.2 | Previous generation; cheaper but lacks the hybrid attention efficiency and 1M context. | 160K tokens | Yes | $0.33 / $0.48 | Low-cost coding & chat |
| Grok 4.3 | Proprietary alternative with comparable pricing but closed weights. | 1M tokens | No | $1.42 / $2.83 | Real-time search & reasoning |
The open-weight leader in cost-effective long-context reasoning.
Use cases
What it is good for
- 01Repository-scale agentic coding and automated software engineering.
- 02Analyzing extremely long documents, legal contracts, or full books within the 1M context window.
- 03Complex mathematical reasoning and multi-step scientific problem solving.
- 04Structured data extraction and JSON generation from massive unstructured datasets.
Prompting
Getting better results
Utilize its native tool use and function calling capabilities for complex agentic workflows.
For massive codebases, feed the entire repository structure into the 1M context window to get holistic refactoring suggestions.
Use structured output schemas (JSON) to reliably parse complex reasoning steps.
Version history
Initial flagship MoE model.
Incremental upgrade with improved coding and reasoning.
Current flagship with 1M context, hybrid attention, and 1.6T parameters.
FAQ
Frequently asked questions
DeepSeek V4 Pro is a flagship 1.6-trillion parameter Mixture-of-Experts (MoE) language model released by DeepSeek in April 2026. It features 49 billion active parameters, a 1-million-token context window, and advanced reasoning capabilities optimized for coding and agentic tasks.
On Venice, DeepSeek V4 Pro is billed per token at $1.73 per 1M input tokens and $3.80 per 1M output tokens, with cached inputs priced at $0.33 per 1M.
DeepSeek V4 Pro is an open-weight model released under the permissive MIT license. While you can download and self-host the weights for free, running it on Venice's hosted API incurs a low per-token cost.
Yes. DeepSeek V4 Pro natively supports tool use (function calling), reasoning, web search, and structured JSON output, making it highly optimized for agentic workflows.
DeepSeek V4 Pro offers comparable agentic coding and reasoning performance to Claude Sonnet 4.6 but at a fraction of the cost ($1.73/$3.80 vs $3.60/$18.00 per million tokens) and with the added sovereignty of open weights.
Venice forwards your requests anonymized without storing your prompt history. However, because this model is served via a third-party provider, that provider may retain and train on prompt data per their own policies.
DeepSeek V4 Pro supports a massive 1-million-token (1,000K) context window, allowing you to process entire codebases, technical manuals, or extensive documents in a single prompt.
Run DeepSeek V4 Pro privately
No prompt logging. No data used for training.