DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 is a high-performance, agentic-focused model with 284B parameters and 13B active, now officially released with enhanced tool use and reasoning.
Overview
What is DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 is a high-performance AI model from DeepSeek AI, released on July 31, 2026. It features 284B total parameters with 13B active at inference, optimized for agentic workflows, function calling, and code generation, now publicly available with MIT-licensed open weights.
Running it privately on Venice
On Venice, DeepSeek V4 Flash 0731 runs with zero retention — your prompts are never stored or used for training. It supports tool use, web search, and structured output, making it ideal for private, uncensored agent workflows. You get full sovereignty over sensitive tasks without sacrificing performance.
Assessment
Strengths and limitations
- Exceptional agentic performance: outperforms DeepSeek-V4-Pro-Preview on all published benchmarks despite fewer active parameters.
- Supports function calling, web search, and code-optimized output for real-world automation tasks.
- 1M token context window enables long-document reasoning and complex codebase navigation.
- Open weights under MIT license allow self-hosting, fine-tuning, and full transparency.
- Highly cost-efficient with Venice’s zero-retention privacy and optional caching discounts.
- Not uncensored: content moderation policies apply per DeepSeek’s terms.
- No end-to-end encryption or TEE isolation on Venice, limiting compliance for some regulated use cases.
- Verbosity can be high: may generate more tokens than necessary for some tasks.
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
Variants
DeepSeek V4 Flash 0731 serving tiers
DeepSeek V4 Flash 0731 runs on Venice in 2 serving tiers: the same model at different speeds and prices. Pick by latency needs; each tier is its own model id on the API.
| Tier | What it is | Price / 1M tokens | Context | Model ID |
|---|---|---|---|---|
| Standardflagship | Full-quality serving at standard pricing | $0.17 in · $0.35 out | 1,000K tokens | deepseek-v4-flash-0731 |
| Fast | The same model served with faster output | $0.35 in · $0.70 out | 1,000K tokens | deepseek-v4-flash-0731-fast |
Pricing and context come straight from the Venice model API and refresh with every catalog ingest. The specs and pricing on this page are for the standard tier; pass the model id of the tier you want to the API.
DeepSeek V4 Flash 0731 Standard
Full-quality serving at standard pricing. $0.17 in · $0.35 out per 1M tokens, 1,000K tokens context.
deepseek-v4-flash-0731DeepSeek V4 Flash 0731 Fast
The same model served with faster output. $0.35 in · $0.70 out per 1M tokens, 1,000K tokens context.
deepseek-v4-flash-0731-fastSpecifications
Datasheet
- Maker
- DeepSeek AI
- License
- MIT
- Context window
- 1,000K tokens
- Released
- July 31, 2026
- Architecture
- CSA+HCA backbone with speculative decoding (DSpark)
- Parameters
- 284B total, 13B active
- Open/closed
- Open weights (MIT license)
- Max output
- 32K tokens
- Capabilities
- Function calling, Reasoning, Web search, Code-optimized
- Privacy on Venice
- Private — zero retention
- Available on Venice since
- Jul 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-flash-0731",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $0.17 per 1M input tokens and $0.35 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 | Max resolution | Strongest at | Open weights | Price (Venice) |
|---|---|---|---|---|
| DeepSeek V4 Flash 0731 | N/A | Agentic coding & automation | No | $0.17 in · $0.35 out / 1M |
| Claude Opus 5 | N/A | Reasoning & accuracy | No | $6 in · $30 out / 1M |
| Google Gemma 4 31B Instruct | N/A | Efficiency & open weights | Yes | $0.12 in · $0.36 out / 1M |
| GLM 5.1 | N/A | Multilingual & enterprise | Yes | $1.54 in · $4.84 out / 1M |
Top-tier agentic performance with open weights and 1M context.
Use cases
What it is good for
- 01Autonomous coding agents and software development pipelines.
- 02Private research assistants with web search and citation.
- 03Long-context document analysis and summarization across legal or financial datasets.
- 04Tool-integrated workflows like API orchestration, data scraping, and task automation.
- 05Cost-sensitive production deployments where open weights and caching reduce TCO.
Prompting
Getting better results
Use structured JSON output mode for reliable parsing in agent workflows.
Leverage web search capability when up-to-date information is required.
Set temperature=1.0 and top_p=0.95 for maximum reasoning effort in complex tasks.
Use cached input for repeated context to take advantage of 98% cost reduction.
Version history
Initial preview release with lower agentic performance.
Official release with re-post-training, open weights, and enhanced agent capabilities.
FAQ
Frequently asked questions
DeepSeek V4 Flash 0731 is a high-performance AI model from DeepSeek AI, released on July 31, 2026. It features 284B total parameters with 13B active at inference, optimized for agentic workflows, function calling, and code generation, now publicly available with MIT-licensed open weights.
On Venice, DeepSeek V4 Flash 0731 costs $0.17 per 1M input tokens and $0.35 per 1M output tokens. Cached input is billed at just $0.04 per 1M tokens, offering significant savings for repeated context.
Yes. DeepSeek V4 Flash 0731 is open weights under the permissive MIT license, allowing free use, modification, and self-hosting. It is not subscription-based and can be run independently.
Yes. DeepSeek V4 Flash 0731 supports function calling and tool use, making it ideal for building autonomous agents, integrating APIs, and automating complex workflows.
DeepSeek V4 Flash 0731 supports a 1,000K (1M) token context window, enabling long-context reasoning, document analysis, and codebase-level understanding.
Yes. DeepSeek V4 Flash 0731 supports web search, allowing it to retrieve and cite up-to-date information during inference, which is useful for research and real-time data tasks.
DeepSeek V4 Flash 0731 excels in agentic coding and automation with open weights and lower cost, while Claude Opus 5 leads in general reasoning and accuracy but is closed and 35x more expensive. Choose Flash for open, cost-efficient agents; Opus for high-stakes reasoning.
Run DeepSeek V4 Flash 0731 privately
No prompt logging. No data used for training.