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DeepSeek V4 Flash 0731 (NovitaAI)

DeepSeek’s official V4 Flash 0731 release replaces the earlier preview and is aimed particularly at agentic software work. It retains the model structure used by DeepSeek-V4-Flash-DSpark, including an attached speculative decoding module, while exposing low, high, and max reasoning-effort settings. Its published evaluation table shows substantial gains over both the Flash preview and the Pro preview across Terminal Bench 2.1, NL2Repo, Cybergym, DeepSWE, Toolathlon-Verified, Agents’ Last Exam, and AutomationBench Public. The same results also show it exceeding the Pro preview on DeepSeek’s internal DSBench-FullStack and DSBench-Hard sets, supporting its practical fit for coding-agent and repository workflows.

Independent Artificial Analysis testing found a pronounced intelligence improvement over the earlier V4 Flash, including much stronger real-world agent work and lower hallucination behavior, while noting that the underlying model size was unchanged. The release also supports speculative decoding through vLLM and SGLang, giving deployers options for accelerating generation, and DeepSeek publishes the weights under the MIT License. Overall, it is a capable open-weight choice for developers and organizations seeking strong coding-agent results, adjustable reasoning effort, and local deployment flexibility, with its largest practical focus being software-engineering agents rather than general-purpose conversational use.

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LLM Gateway
Model key
novita/deepseek-v4-flash-0731
Release date
Jul 31, 2026
Last updated
Jul 31, 2026
Knowledge cutoff
2025-05
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.14
Output token cost
$0.28

Limits

Output tokens
393,216 tokens
Context window
1,050,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about DeepSeek V4 Flash 0731 (NovitaAI)

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CoverageAnalysis

Artificial Analysis independently scored DeepSeek V4 Flash 0731 at 50 on its Intelligence Index, 10 points above the earlier V4 Flash and one point behind GPT-5.6 Luna at max. Its agentic GDPval-AA v2 Elo rose to 1559 from 1189, while Terminal-Bench 2.1 increased 17 points to 79% and τ³-Bench Banking increased eight points to 31%. The evaluation says the checkpoint retains a 1M-token context window and the prior model’s 284B total and 13B active parameters. Its AA-Omniscience Index improved by seven points to -16 because the hallucination rate fell 12 points to 84%, while overall accuracy remained unchanged, and the model reached the analysis provider’s Intelligence-versus-cost Pareto frontier.

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Coverage

DeepSeek’s official model card names DeepSeek-V4-Flash-0731 as the release that supersedes the V4 Flash preview, with substantially improved agentic capabilities and the same structure as V4-Flash-DSpark, including an attached speculative decoding module. The vendor reports 82.7 on Terminal Bench 2.1, 54.2 on NL2Repo, 54.4 on DeepSWE, and 70.3 on Toolathlon-Verified. For developers, the checkpoint supports low, high, and max reasoning effort but does not include a Jinja chat template; DeepSeek instead provides encoding scripts for OpenAI-compatible messages and response parsing. Its vLLM guide enables DSpark speculative decoding with a seven-token speculative configuration, while the benchmark table uses DeepSeek’s unreleased Harness and includes internal DSBench datasets.

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