Capability
Unranked
field median 56.3
Not eligible for a public rank
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Follow model changesReleased Sep 10, 2026 — see all recent releases
Data as of September 10, 2026 · How the score is built
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Published rows are visible, but no category has enough eligible evidence for a comparative rank.
22 published rows leave some tracked benchmark slots empty. Independent runtime speed has not been measured.
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 56.3
Not eligible for a public rank
Price
$0.30input / $1.20 output
input median $1
cached $0.006 · blended $0.75
Speed
Not measured
field median 92 tok/s
Time to first token not measured
Context
1Mtokens
field median 256,000
Maximum output length is tracked separately
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.
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
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 parametersScores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank Not rankedWeight 22%8 benchmarksVerified | 81.2 | Not ranked | Not available | 22% | 8 benchmarks | Verified |
| CodingWeight 20%6 benchmarksVerified | Score pending | Not ranked | Not available | 20% | 6 benchmarks | Verified |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeRank Not rankedWeight 12%3 benchmarksVerified | 53.4 | Not ranked | Not available | 12% | 3 benchmarks | Verified |
| MathWeight 5%1 benchmarkVerified | Score pending | Not ranked | Not available | 5% | 1 benchmark | Verified |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%3 benchmarksVerified | Score pending | Not ranked | Not available | 12% | 3 benchmarks | Verified |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
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.
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| CodeforcesCodeforces Rating | Score3471.0 | Versus best verified row Best verified: DeepSeek V4.1 Flash · 3471.0 | GapBest verified | WeightDisplay only | Provider exact |
| Terminal-Bench 2.1Terminal-Bench 2.1 (provider run) | Score90.6% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 90.6% | GapBest verified | WeightDisplay only | Provider exact |
| terminalBench3 | Score30% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 30% | GapBest verified | WeightDisplay only | Provider exact |
| DeepSWE | Score74.2% | Versus best verified row Best verified: Muse Spark 1.3 · 75.4% | Gap1.2 behind | WeightDisplay only | Provider exact |
| ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch? | Score20.3% | Versus best verified row Best verified: Claude Opus 5 · 93.0% | Gap72.7 behind | WeightDisplay only | Provider exact |
| NL2Repo | Score65.4% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 65.4% | GapBest verified | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| AutomationBench | Score54.8% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 54.8% | GapBest verified | WeightWeighted 10% | Provider exact |
| Terminal-Bench 2.1Terminal-Bench 2.1 (provider run) | Score90.6% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 90.6% | GapBest verified | WeightDisplay only | Provider exact |
| terminalBench3 | Score30% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 30% | GapBest verified | WeightDisplay only | Provider exact |
| Terminal-Bench 4.0 | Score31.20% | Versus best verified row Best verified: Claude Mythos 5.1 · 60.90% | Gap29.7 behind | WeightDisplay only | Provider exact |
| CyberGym | Score88.1% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 88.1% | GapBest verified | WeightDisplay only | Provider exact |
| ExploitGym | Score15.3% | Versus best verified row Best verified: GPT-6 Astra · 42.4% | Gap27.1 behind | WeightDisplay only | Provider exact |
| HLE w/ toolsHumanity's Last Exam with tools | Score63.9% | Versus best verified row Best verified: Claude Opus 5 · 64.7% | Gap0.8 behind | WeightDisplay only | Provider exact |
| Agents' Last Exam | Score31.8% | Versus best verified row Best verified: GPT-6 Astra · 59.3% | Gap27.5 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLEHumanity's Last Exam | Score36.8% | Versus best verified row Best verified: Claude Fable 5.1 · 65% | Gap28.2 behind | WeightWeighted 35% | Provider exact |
| GPQAGraduate-Level Google-Proof Q&A | Score90.9% | Versus best verified row Best verified: GPT-6 Astra · 96% | Gap5.1 behind | WeightWeighted 7% | Provider exact |
| GPQA-DGPQA Diamond | Score90.9% | Versus best verified row Best verified: GPT-6 Astra · 96.0% | Gap5.1 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Apex | Score65.6% | Versus best verified row Best verified: Hy4 preview · 74.2% | Gap8.6 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Chartography (tools)Chartography with image and code tools | Score78.9% | Versus best verified row Best verified: Claude Opus 5 · 83.0% | Gap4.1 behind | WeightDisplay only | Provider exact |
| BabyVision w/ PythonBabyVision with Python | Score89.6% | Versus best verified row Best verified: Qwen3.8 Max · 91.3% | Gap1.7 behind | WeightDisplay only | Provider exact |
| ZeroBench w/ PythonZeroBench_main with Python | Score49.0% | Versus best verified row Best verified: Qwen3.8 Max · 49.0% | GapBest verified | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SEC-Bench Pro | Score62.8% | Versus best verified row Best verified: GPT-6 Astra · 85.4% | Gap22.6 behind | WeightDisplay only | Provider exact |
The sequence follows explicit supersedes links. A successor's displayed score stays at least 0.1 points above its predecessor; raw benchmark rows do not move. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Jul 31, 2026
DeepSeek V4 Flash 0731Not publicly ranked · $0.14 / $0.28
Sep 10, 2026 · you are here
DeepSeek V4.1 FlashNot publicly ranked · $0.3 / $1.2
Flash-reasoning
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
We track DeepSeek V4.1 Flash, but the public leaderboard excludes this profile until enough non-generated benchmark coverage is available. Only published rows appear above.
DeepSeek V4.1 Flash 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.
Released September 10, 2026 as the smallest model in DeepSeek's new Causal Encoder-Decoder architecture family: 552B backbone parameters, 8B activated per token during prefill and 16B during decode, native image-and-text input, a 1M-token context window, and MIT-licensed weights on Hugging Face. The DeepSeek API serves it as `deepseek-flash` with thinking and non-thinking modes, tool calls, the Responses and Anthropic formats, and vision input. DeepSeek retired V4 Flash and V4 Flash Vision Exp the same day; the legacy `deepseek-v4-flash` and `deepseek-v4-flash-vision-exp` IDs temporarily route here. DeepSeek also says V4 Pro is being phased out: from 04:00 UTC on September 14, 2026, `deepseek-v4-pro` requests route to V4.1 Flash at V4.1 Flash rates until V4.1 Pro launches.
Official exact-value snapshot from the DeepSeek-V4.1-Flash model card and technical report published September 10, 2026. All instruct rows use the maximum reasoning effort (reasoning_effort=100), temperature 1.0, and top_p 0.95. Code-agent rows (Terminal-Bench 2.1, 3.0, and 4.0, DeepSWE v1.1, NL2Repo-Bench, ProgramBench) use the Minimal mode of DeepSeek Harness with a 1M-token context, except DeepSWE v1.1, which uses mini-SWE-agent, and SEC-Bench Pro, which uses the Claude Code harness; the visual agent rows (Chartography, BabyVision, ZeroBench) use the Claude Code harness with a 512K context; Agents' Last Exam and AutomationBench use their official scaffolds. Every launch row is provider-run and harness-specific, so it stays display-only and out of weighted ranking coverage. HLE is the full set at 36.8; DeepSeek reports 39.1 on the text-only subset. ProgramBench is the Almost@1 metric. NL2Repo-Bench is stored at the technical report's 65.4, which DeepSeek's changelog repeats; the model card table prints 64.0 for the same row. MathArena Apex is the September 2026 edition, on which DeepSeek re-scores V4 Pro at 65.3 and V4 Flash at 58.6, so it is not comparable with the Apex values stored from the April V4 report. The base-model table on the model card (MMLU-Pro 74.1, HumanEval 79.4, GSM8K 93.0, and the rest) is pretraining evidence for a separate checkpoint and is not stored on this instruct row.
Its explicit predecessor is DeepSeek V4 Flash 0731. 22 of 428 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
DeepSeek · Model release
Radar confirmed these at the source. Use DeepSeek V4.1 Flash in your work? Explore Radar to follow supported changes and choose your alerts.
DeepSeek V4.1 Flash has 22 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.
DeepSeek V4.1 Flash 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.
DeepSeek V4.1 Flash 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.
DeepSeek V4.1 Flash 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.
DeepSeek V4.1 Flash 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.
DeepSeek V4.1 Flash has source-displayable benchmark coverage for multimodal and grounded 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.
DeepSeek V4.1 Flash 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.
No. DeepSeek V4.1 Flash currently has 22 source-displayable rows across 428 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.
DeepSeek V4.1 Flash 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.
Related resources
Last updated September 10, 2026. Runtime fields remain blank until a sourced snapshot exists.
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