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DeepSeek V4 Flash 0731

DeepSeek's official July 2026 efficient MoE model — 1M context, agentic tool use, and speculative decoding at ultra-low cost.

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What is DeepSeek V4 Flash 0731?

DeepSeek V4 Flash 0731 is the official July 2026 release of DeepSeek's efficient mixture-of-experts language model, succeeding the April preview with enhanced agentic reasoning, coding, and tool-use capabilities. It features a 1 million-token context window, speculative decoding for speed, and natively supports the Responses API format.

Use DeepSeek V4 Flash 0731 privately on Venice

On Venice, DeepSeek V4 Flash 0731 runs under a private, zero-retention tier — your prompts are not stored or used for training. You get access to its reasoning, tool use, web search, and code-optimized capabilities at a fraction of Big-Tech prices, with no surveillance. It is a fast, permissionless way to run a frontier agentic model while keeping full data sovereignty.

Private (zero retention)
No prompt training
TEE · hardware enclave
End-to-end encrypted

What can DeepSeek V4 Flash 0731 do?

Strengths
  • Extremely cost-efficient agentic reasoning and coding — benchmarked by DeepSeek to outperform the larger V4-Pro-Preview on Terminal Bench 2.1, Toolathlon, and CyberGym despite far fewer activated parameters.
  • Native tool use / function calling, web search, and structured JSON output make it a strong drop-in for autonomous agents and Codex-style workflows.
  • 1 million-token context window supports large codebases and long documents.
  • Speculative decoding module attached to the MoE architecture yields low latency for high-volume workloads.
  • Supports both thinking (default) and non-thinking modes, letting developers trade reasoning depth for speed.
Limitations
  • Closed weights — cannot be self-hosted or fine-tuned outside Venice.
  • Not uncensored — carries standard safety alignment.
  • Benchmark scores cited by DeepSeek use their own evaluation harness (max effort, temperature=1.0, top_p=0.95), so independent replication is advised before betting on exact numbers.
  • Does not run inside a TEE or with end-to-end encryption on Venice (private zero-retention tier, but not hardware-isolated).
  • On some tasks, premium rivals like Opus-4.8 still score higher (e.g., AutomationBench Public, DSBench-Hard).

DeepSeek V4 Flash 0731 capabilities

How to use DeepSeek V4 Flash 0731 via API

Venice exposes an OpenAI-compatible API. Swap your base URL and call deepseek-v4-flash-0731.

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." }]
  }'

Specifications

MakerDeepSeek
ReleasedJuly 31, 2026
ArchitectureMixture-of-Experts (MoE) with speculative decoding
Parameters284B total / 13B active
Open weightsNo — proprietary
Context window1,000K tokens
Max output32.768K tokens
CapabilitiesFunction calling, Reasoning, Web search, Code-optimized
Privacy on VenicePrivate — zero retention
Available on Venice sinceJul 2026
LicenseProprietary

Pricing

Billed per token on Venice: $0.07 per 1M input tokens and $0.14 per 1M output tokens.

Input / 1M tokens
$0.07
Output / 1M tokens
$0.14
Cached input / 1M
$0.01

New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.

DeepSeek V4 Flash 0731 vs alternatives

ModelContext windowKey strengthsOpen weightsPrice (Venice)
DeepSeek V4 Flash 07311M tokensAgentic coding, tool use, reasoningNo$0.07 in · $0.14 out / 1M
DeepSeek V3.2160K tokensGeneral reasoning, open weightsYes$0.33 in · $0.48 out / 1M
Claude Sonnet 4.61M tokensStrong reasoning, safetyNo$3.60 in · $18 out / 1M
Grok 4.5500K tokensReal-time knowledge, xAI ecosystemNo$2.27 in · $6.80 out / 1M
Kimi K31M tokensLong context, open weightsYes$3.75 in · $18.75 out / 1M

The official July 2026 refresh — same MoE architecture, retrained for agentic work and tool use at the lowest price per token in its class.

What is DeepSeek V4 Flash 0731 good for?

  • High-volume coding agents and autonomous software engineering (DeepSWE, NL2Repo).
  • Long-context document analysis and RAG with 1M tokens of context.
  • Multi-step business automation and tool-calling workflows.
  • Cost-sensitive production assistants where reasoning and tool use are needed at low cost.
  • Real-time code completion and terminal-based agent tasks.

Prompting tips

  • Enable thinking mode for complex agentic tasks; switch to non-thinking for simple completions to save tokens and latency.
  • Use the Responses API format when building Codex-style agents — it is natively supported.
  • Set temperature to 1.0 and top_p to 0.95 to match DeepSeek's own benchmark harness if you are evaluating agentic performance.
  • Leverage structured JSON output for reliable tool chaining and business workflow automation.
  • Keep prompts within the 1M context budget, but note that very long contexts increase per-request cost proportionally.

Version history

DeepSeek V4 Flash (Preview)
2026-04

Initial preview release with 1M context and basic agentic features.

DeepSeek V4 Flash 0731
2026-07

CurrentOfficial public-beta refresh with enhanced agentic capabilities, Responses API support, and Codex adaptations.

Frequently asked questions

DeepSeek V4 Flash 0731 is the official July 2026 release of DeepSeek's efficient mixture-of-experts language model. It upgrades the April preview with stronger agentic reasoning, coding, and tool-use capabilities, adds native Responses API support, and keeps the same 284B total / 13B active parameter scale.

On Venice, DeepSeek V4 Flash 0731 costs $0.07 per 1M input tokens and $0.14 per 1M output tokens, with cached input priced at $0.01 per 1M tokens. That makes it one of the cheapest reasoning-capable models on the platform.

It is not free — inference is billed per token on Venice. The weights are not openly available for self-hosting on Venice, and the model is served via API only. If you need an open-weight alternative, DeepSeek V3.2 is available on Venice with open weights.

Yes. It supports function calling, structured JSON output, and the Responses API format, making it well-suited for agentic workflows, Codex-style agents, and multi-step automation.

The model supports up to 1,000,000 tokens of context and can generate up to 32,768 tokens in a single response, allowing it to process very large codebases or long documents.

DeepSeek V4 Flash 0731 wins on price and agentic coding benchmarks like Terminal Bench 2.1, while Claude Sonnet 4.6 may offer more conservative safety alignment and broader general reasoning. For cost-sensitive coding agents, Flash is hard to beat; for nuanced creative writing or safety-critical tasks, Sonnet remains a strong rival.

Yes. Venice processes DeepSeek V4 Flash 0731 under a private, zero-retention tier — prompts are not stored, profiled, or used for training. However, it does not currently run inside a TEE or with end-to-end encryption.

Yes. The model supports web search as a capability on Venice, allowing it to retrieve current information to augment its answers.

Yes. It defaults to a thinking mode for step-by-step reasoning and offers a non-thinking mode for faster, simpler completions where deep reasoning is unnecessary.

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Run DeepSeek V4 Flash 0731 privately.

No prompt logging. No data used for training. Free to start — no credit card.

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