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DeepSeek: DeepSeek V4 Flash 0731 (batch)

deepseek/deepseek-v4-flash-0731:batch

Model weights

DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows. This is the GA release of DeepSeek V4 Flash.

Modalities
In / out price
$0.048 / $0.144per 1M
Context
1.0M
Released
Jul 31, 2026

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input
$0/M tokens
Output
$0/M tokens
Price history
No effective price data for this selection

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

AutoExacto benchmarks
GPQA DiamondTAU-BenchMancer 290.6%78.7%Morph90.4%78.0%Baidu90.7%77.2%Together87.2%80.7%DeepInfra90.8%76.7%
+24 more providers

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Not enough uptime data to display yet.

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for DeepSeek: DeepSeek V4 Flash 0731 (batch) (Artificial Analysis, Design Arena and Vals AI)
SourceBenchmarkScore
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) Coding Index69.1
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) Agentic Index41.0
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) GPQA Diamond90.8%
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) HLE38.6%
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) AA-LCR79.7%
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) τ-Bench Banking39.4%
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) GDPval-AA46.8%
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) CritPt16.6%
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) SciCode50.3%
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) Terminal-Bench 4.012.1%
Artificial AnalysisDeepSeek V4 Flash 0731 (Max) Terminal-Bench 2.178.7%
Design ArenaDeepSeek-V4-Flash-0731 Models Arena 3D Elo1188
Design ArenaDeepSeek-V4-Flash-0731 Models Arena Asciiart Elo1092
Design ArenaDeepSeek-V4-Flash-0731 Models Arena Code Categories Elo1219
Design ArenaDeepSeek-V4-Flash-0731 Models Arena Data Visualization Elo1169
Design ArenaDeepSeek-V4-Flash-0731 Models Arena Game Development Elo1198
Design ArenaDeepSeek-V4-Flash-0731 Models Arena SVG Elo1170
Design ArenaDeepSeek-V4-Flash-0731 Models Arena UI Component Elo1227
Design ArenaDeepSeek-V4-Flash-0731 Models Arena Website Elo1230
Vals AIDeepSeek V4 Flash 0731 BioMysteryBench64.4%
Vals AIDeepSeek V4 Flash 0731 Code Migration38.6%
Vals AIDeepSeek V4 Flash 0731 CorpFin v261.8%
Vals AIDeepSeek V4 Flash 0731 CyberBench v1.172.1%
Vals AIDeepSeek V4 Flash 0731 EMB57.0%
Vals AIDeepSeek V4 Flash 0731 Finance Agent (v2)49.5%
Vals AIDeepSeek V4 Flash 0731 GPQA Diamond89.9%
Vals AIDeepSeek V4 Flash 0731 Harvey's Legal Agent Benchmark v18.3%
Vals AIDeepSeek V4 Flash 0731 IOI32.7%
Vals AIDeepSeek V4 Flash 0731 LiveCodeBench87.3%
Vals AIDeepSeek V4 Flash 0731 LegalBench77.7%
Vals AIDeepSeek V4 Flash 0731 Legal Research Bench30.3%
Vals AIDeepSeek V4 Flash 0731 MedCode41.4%
Vals AIDeepSeek V4 Flash 0731 MedScribe80.4%
Vals AIDeepSeek V4 Flash 0731 MMLU Pro86.2%
Vals AIDeepSeek V4 Flash 0731 ProgramBench0.0%
Vals AIDeepSeek V4 Flash 0731 ProofBench v1.156.0%
Vals AIDeepSeek V4 Flash 0731 SkillsBench50.7%
Vals AIDeepSeek V4 Flash 0731 SWE-bench88.8%
Vals AIDeepSeek V4 Flash 0731 Tax Agent Bench28.1%
Vals AIDeepSeek V4 Flash 0731 TaxEval v270.7%
Vals AIDeepSeek V4 Flash 0731 Terminal-Bench 4.018.7%
Vals AIDeepSeek V4 Flash 0731 Terminal-Bench-Science4.3%
Vals AIDeepSeek V4 Flash 0731 Vals Index48.0%
Vals AIDeepSeek V4 Flash 0731 Vibe Code Bench v1.174.7%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Not enough data for apps using this model yet.

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

Not currently available through EU in-region routing. In-region routing docs

Documentation

Guides, cookbooks, blog posts, and tools for building with DeepSeek: DeepSeek V4 Flash 0731 (batch) on OpenRouter.

Frequently asked questions

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