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BenchLM

Data as of September 27, 2026 · How the score is built

Superseded.DeepSeek has newer models in this line:DeepSeek V4.1 Flash
SupersededOpen WeightReasoning

Released Jul 31, 20261M context

DeepSeek V4 Flash 0731

Decision readingDeepSeek V4 Flash 0731 is tracked, but not publicly ranked yet. The profile exposes 42 sourced benchmark rows and leaves unsupported fields blank until a published record exists.

Released Jul 31, 2026 — see all recent releases

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

Unranked

field median 50.2Not eligible for a public rank

Price

$0.14input / $0.28 output

input median $0.97cached $0.003 · blended $0.21

Speed

221tok/s

field median 91 tok/sFirst token 10.17 s

Context

1Mtokens

field median 256,000Maximum output length is tracked separately

Strongest published evidence

Published rows are visible, but no category has enough eligible evidence for a comparative rank.

Validate before choosing

42 published rows leave some tracked benchmark slots empty.

Source-linked · 42 displayable benchmark rows

Follow model changes

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank Not rankedWeight 22%11 benchmarksVerified
52.0
CodingRank Not rankedWeight 20%15 benchmarksVerified
50.8
ReasoningRank Not rankedWeight 17%4 benchmarksVerified
57.0
MultimodalWeight 12%0 benchmarksNot measured
Not measured
KnowledgeRank Not rankedWeight 12%8 benchmarksVerified
61.3
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathRank Not rankedWeight 5%4 benchmarksVerified
79.9

42 of 486 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic11/11 verified
  2. Coding15/15 verified
  3. Reasoning4/4 verified
  4. MultimodalNot measured
  5. Knowledge8/8 verified
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. Math4/4 verified
Verified sourceProvisionalNot measured

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding15 rows
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench ProScore52.6%Versus best verified row

Best verified: Claude Opus 5.5 · 89.9%

Gap37.3 behindWeight26% ref. weight
LiveCodeBench (Vals)LiveCodeBench, Vals AI runScore87.3%Versus best verified row

Best verified: Claude Fable 5.1 · 90.5%

Gap3.2 behindWeight8% ref. weight
SWE MultilingualScore73.3%Versus best verified row

Best verified: Claude Opus 5.5 · 93.9%

Gap20.6 behindWeight5% ref. weight
VulcanBench v3Score88.4%Versus best verified row

Best verified: Grok 4.5 · 89.9%

Gap1.5 behindWeight3% ref. weight
Terminal-Bench 2.0Score56.9%Versus best verified row

Best verified: GPT-5.5 · 82.0%

Gap25.1 behindWeightScored in Agentic
DeepSWEScore54.4%Versus best verified row

Best verified: Muse Spark 1.3 · 75.4%

Gap21 behindWeightDisplay only
LiveCodeBench Pass@1-COTLiveCodeBench Pass@1 with Chain-of-ThoughtScore91.6%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 93.5%

Gap1.9 behindWeightDisplay only
CodeforcesCodeforces RatingScore3052.0Versus best verified row

Best verified: DeepSeek V4.1 Flash · 3471.0

Gap419 behindWeightDisplay only
SWE-bench VerifiedSoftware Engineering Benchmark VerifiedScore79%Versus best verified row

Best verified: Claude Opus 5 · 96%

Gap17 behindWeightDisplay only
Terminal-Bench 2.1Score82.7%Versus best verified row

Best verified: SWE-2 · 92.8%

Gap10.1 behindWeightDisplay only
NL2RepoScore54.2%Versus best verified row

Best verified: DeepSeek V4.1 Flash · 65.4%

Gap11.2 behindWeightDisplay only
DSBench-FullStackDeepSeek DSBench FullStackScore68.7%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 71.1%

Gap2.4 behindWeightDisplay only
DSBench-HardDeepSeek DSBench HardScore59.6%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 67.2%

Gap7.6 behindWeightDisplay only
OpenHarmony BenchOpenHarmony Bench v1.0Score53.8%Versus best verified row

Best verified: Qwen3.8 Max · 60.8%

Gap7 behindWeightDisplay only
SWE-bench (Vals)SWE-bench, Vals AI runScore88.8%Versus best verified row

Best verified: Claude Opus 5 · 97.0%

Gap8.2 behindWeightDisplay only
Agentic11 rows
Agentic benchmark values, best verified comparison, weight, and source status
BrowseCompScore73.2%Versus best verified row

Best verified: Atria Dawn Preview · 92.5%

Gap19.3 behindWeight8% ref. weight
Terminal-Bench 2.0Score56.9%Versus best verified row

Best verified: GPT-5.5 · 82%

Gap25.1 behindWeight7% ref. weight
MCP AtlasScore69%Versus best verified row

Best verified: Muse Spark 1.1 · 88.1%

Gap19.1 behindWeight4% ref. weight
Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI runScore67.0%Versus best verified row

Best verified: GPT-6 Astra · 87.3%

Gap20.3 behindWeight3% ref. weight
HLE w/ toolsHumanity's Last Exam with toolsScore45.1%Versus best verified row

Best verified: Claude Opus 5.5 · 67.7%

Gap22.6 behindWeight3% ref. weight
ToolathlonScore47.8%Versus best verified row

Best verified: Muse Spark 1.1 · 75.6%

Gap27.8 behindWeight3% ref. weight
Terminal-Bench 2.1Score82.7%Versus best verified row

Best verified: SWE-2 · 92.8%

Gap10.1 behindWeightDisplay only
AutomationBenchScore25.1%Versus best verified row

Best verified: DeepSeek V4.1 Flash · 54.8%

Gap29.7 behindWeightDisplay only
Toolathlon-VerifiedScore70.3%Versus best verified row

Best verified: Claude Opus 5 · 80.6%

Gap10.3 behindWeightDisplay only
Agents' Last ExamScore25.2%Versus best verified row

Best verified: GPT-6 Astra · 59.3%

Gap34.1 behindWeightDisplay only
CyberGymScore76.7%Versus best verified row

Best verified: MiMo-V2.6-Flash · 95.1%

Gap18.4 behindWeightDisplay only
Reasoning4 rows
Reasoning benchmark values, best verified comparison, weight, and source status
ARC-AGI-2Abstraction and Reasoning Corpus for AGI v2Score61.4%Versus best verified row

Best verified: GPT-6 Astra · 95%

Gap33.6 behindWeightWeighted 25%
MRCR 1MScore78.7%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 83.5%

Gap4.8 behindWeightDisplay only
CorpusQA 1MScore60.5%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 62.0%

Gap1.5 behindWeightDisplay only
ARC-AGI-1ARC-AGI-1 Semi-Private EvaluationScore89.00%Versus best verified row

Best verified: GPT-6 Astra · 98.50%

Gap9.5 behindWeightDisplay only
Knowledge8 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore34.8%Versus best verified row

Best verified: Claude Fable 5.1 · 65%

Gap30.2 behindWeight44% ref. weight
MMLU-ProMassive Multitask Language Understanding ProfessionalScore86.2%Versus best verified row

Best verified: Qwen3.7 Max · 89.6%

Gap3.4 behindWeight6% ref. weight
MMLU-Pro (Vals)MMLU-Pro, Vals AI runScore86.2%Versus best verified row

Best verified: Claude Fable 5.1 · 92.4%

Gap6.2 behindWeight6% ref. weight
GPQAGraduate-Level Google-Proof Q&AScore88.1%Versus best verified row

Best verified: GPT-6 Astra · 96%

Gap7.9 behindWeight3% ref. weight
GPQA Diamond (Vals)GPQA Diamond, Vals AI runScore89.9%Versus best verified row

Best verified: Gemini 3.1 Pro · 95.5%

Gap5.6 behindWeight2% ref. weight
SimpleQAMeasuring Short-Form Factuality in Large Language ModelsScore34.1%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 57.9%

Gap23.8 behindWeightDisplay only
Chinese-SimpleQAScore78.9%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 84.4%

Gap5.5 behindWeightDisplay only
GPQA-DGPQA DiamondScore88.1%Versus best verified row

Best verified: GPT-6 Astra · 96.0%

Gap7.9 behindWeightDisplay only
Math4 rows
Math benchmark values, best verified comparison, weight, and source status
HMMT Feb 2026Harvard-MIT Mathematics Tournament February 2026Score94.8%Versus best verified row

Best verified: Qwen3.7 Max · 97.1%

Gap2.3 behindWeightWeighted 25%
IMOAnswerBenchScore88.4%Versus best verified row

Best verified: dots3-note Preview · 90.9%

Gap2.5 behindWeightDisplay only
ApexScore33.0%Versus best verified row

Best verified: Hy4 preview · 74.2%

Gap41.2 behindWeightDisplay only
Apex ShortlistScore85.7%Versus best verified row

Best verified: DeepSeek V4 Pro 0813 · 90.2%

Gap4.5 behindWeightDisplay only

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Jul 31, 2026 · you are here

    DeepSeek V4 Flash 0731

    Not publicly ranked · $0.14 / $0.28

  2. Sep 10, 2026

    DeepSeek V4.1 Flash

    Not publicly ranked · $0.3 / $1.2

flash-reasoning · 0731

Radar

DeepSeek V4 Flash 0731 release history

Full release history

Radar confirmed these at the source. Use DeepSeek V4 Flash 0731 in your work? Explore Radar to follow supported changes and choose your alerts.

Radar

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
deepseek-v4-flashDeepSeek-V4.1-Flash release
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Parameters
Not sourced yet
Availability
DeepSeek APIDeepSeek-V4.1-Flash release
Cloud regions
Not tracked yet
Lifecycle
supersededDeepSeek-V4.1-Flash release
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Published at $0.003 per million cached input tokens
Self-host
Open weights available; hardware estimate not sourced
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

We track DeepSeek V4 Flash 0731, but the public leaderboard excludes this profile until enough non-generated benchmark coverage is available. Only published rows appear above.

DeepSeek V4 Flash 0731 is a open weight model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

The existing deepseek-v4-flash API ID now serves DeepSeek-V4-Flash-0731 in public beta. DeepSeek says it has the same architecture and size as Preview with new post-training. Checked again August 1: DeepSeek-V4-Flash-0731 weights are public on Hugging Face under the MIT License, so this row is Open Weight. The Hugging Face card lists 304B parameters because 0731 ships with the DSpark speculative-decoding module attached; the April Preview weights remain a separate checkpoint. Retired September 10, 2026: DeepSeek replaced V4 Flash with DeepSeek-V4.1-Flash, served as `deepseek-flash`. The legacy `deepseek-v4-flash` ID is still accepted but temporarily routes to V4.1 Flash and bills at the Flash rate.

Its explicit predecessor is DeepSeek V4 Flash 0731. 42 of 486 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Last updated September 27, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.

Estimate VRAM from known parameters

Questions

How does DeepSeek V4 Flash 0731 perform overall in AI benchmarks?

DeepSeek V4 Flash 0731 has 42 source-displayable benchmark rows, but it does not qualify for a public overall rank. The available rows remain visible by category without being converted into a site-wide score. Missing evidence stays blank instead of being estimated from an earlier model.

Is DeepSeek V4 Flash 0731 good for knowledge and understanding?

DeepSeek V4 Flash 0731 has source-displayable benchmark coverage for knowledge and understanding, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is DeepSeek V4 Flash 0731 good for coding and programming?

DeepSeek V4 Flash 0731 has source-displayable benchmark coverage for coding and programming, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is DeepSeek V4 Flash 0731 good for mathematics?

DeepSeek V4 Flash 0731 has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is DeepSeek V4 Flash 0731 good for reasoning and logic?

DeepSeek V4 Flash 0731 has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is DeepSeek V4 Flash 0731 good for agentic tool use and computer tasks?

DeepSeek V4 Flash 0731 has source-displayable benchmark coverage for agentic tool use and computer tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is DeepSeek V4 Flash 0731 open source?

DeepSeek V4 Flash 0731 is an open-weight model from DeepSeek. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

Does DeepSeek V4 Flash 0731 have full benchmark coverage on BenchLM?

No. DeepSeek V4 Flash 0731 currently has 56 source-displayable rows across 486 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of DeepSeek V4 Flash 0731?

DeepSeek V4 Flash 0731 has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.

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Compare DeepSeek V4 Flash 0731 with every tracked model507 comparisons