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DeepSeek V4 Flash

DeepSeek

Strongest in Cybersecurity (#18 of 47), weakest in Safety (#267 of 329). Above par in 16 of 32 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 4.8 and DeepSeek V4.1 Flash and ahead of Kimi K2.6 and Mistral Large 4.

§ 1 · Profile

What it is good at

Bars run from 50 — the average of the models each source lists — so right of the line is above par. The middle column is the gap to whoever leads that scope.

Agents56.2#44/298
Knowledge work59.9#47/208
Workflow automation32—/0✱
Coding54.2#47/179
Agentic coding54.3#45/173
Code generation40.2—/20✱
Repository Q&A41.1—/0✱
Reasoning52.7#73/195
Science59.6#27/122
Reasoning55.1#44/147
Mathematics47.4#96/152
Expert reasoning33.8—/0✱
Knowledge52.6#76/197
Academic knowledge56.2#46/123
Human preference60.4#83/354
Human preference60.4#83/354
Professional50.4#88/194
Cybersecurity56.4#18/47
Biology research42.4#25/31
Finance52.5#79/162
Medical50.2#84/149
Legal49.1#97/173
Core abilities49.1#110/199
Language51.5#34/62
Instruction following45.6#40/62
General intelligence49.7#92/178
Safety46.1#267/329
Secure code49.2#161/270
Fairness45.2#187/292
Harm refusal46.6#207/292
Jailbreak resistance40.2#215/268
Toxicity avoidance46.7#217/268

§ 2 · Head to head

What it beats, and what beats it

The same models turn up scope after scope. Counted once: where both were placed, who finished higher. Bars run right for DeepSeek V4 Flash, left for the other.

GPT-5.4 nanowon 18 · lost 3
GPT-5.4 miniwon 17 · lost 3
Qwen3.8 27Bwon 17 · lost 4
Gemini 3.5 Flash-Litewon 17 · lost 4
DeepSeek V3won 19 · lost 5
Llama 4 Scout Instructwon 17 · lost 5
Command Awon 17 · lost 5
Grok 4.1 Fastwon 16 · lost 5
Claude 3.5 Haikuwon 15 · lost 5
GPT-4.1 nanowon 18 · lost 6
GPT-4o miniwon 17 · lost 6
Gemini 2.0 Flashwon 16 · lost 6
Claude Haiku 4.5won 16 · lost 6
MiMo V2.5 Prowon 15 · lost 6
GPT OSS 120Bwon 17 · lost 7
Grok 4.3won 17 · lost 7
DeepSeek V3.2won 16 · lost 7
Grok 3won 15 · lost 7
GPT OSS 20Bwon 14 · lost 7
DeepSeek R1won 15 · lost 8
MiniMax M3won 17 · lost 10
GPT-4.1 miniwon 15 · lost 9
MiniMax M2.7won 13 · lost 8
Gemini 2.5 Flashwon 14 · lost 9
GLM-4.6won 14 · lost 9
Gemma 4 31Bwon 12 · lost 8
GPT-4owon 13 · lost 9
O3 Miniwon 13 · lost 9
Kimi K2won 13 · lost 9
Claude Sonnet 4won 14 · lost 10
GPT-5 nanowon 12 · lost 9
Grok 4won 13 · lost 10
GLM-5.3 Flashwon 15 · lost 12
Mistral Large 4won 13 · lost 11
Kimi K2.6won 13 · lost 11
GPT-6 Lunawon 13 · lost 13
GLM-5.2won 13 · lost 13
Inklingwon 13 · lost 14
GPT-4.1won 11 · lost 12
Claude 3.7 Sonnetwon 10 · lost 11
GPT-5 miniwon 11 · lost 13
Gemini 2.5 Prowon 11 · lost 13
Kimi K2.5won 11 · lost 13
GLM-5.1won 10 · lost 12
O1won 9 · lost 11
O4 Miniwon 10 · lost 13
Qwen3 235B A22B Instructwon 10 · lost 13
Claude Opus 4won 9 · lost 13
Gemini 3.6 Flashwon 11 · lost 16
Kimi K2 Thinkingwon 8 · lost 12
Claude Haiku 5.5won 7 · lost 13
O3won 8 · lost 15
Claude Sonnet 4.6won 8 · lost 15
GPT-5won 8 · lost 16
Claude Sonnet 4.5won 8 · lost 16
Qwen3.7 Maxwon 8 · lost 17
GPT-5.6 Lunawon 8 · lost 20
GPT-5.2won 7 · lost 18
Gemini 3.5 Flashwon 7 · lost 18
MiMo V2.6 Flashwon 6 · lost 16
GPT-5.1won 6 · lost 16
Claude Opus 4.6won 6 · lost 16
Claude Opus 4.5won 5 · lost 15
Gemini 3.7 Flashwon 5 · lost 15
Gemini 3.8 Flashwon 7 · lost 21
Gemini 3.1 Prowon 5 · lost 16
Claude Sonnet 5won 6 · lost 20
Grok 4.5won 6 · lost 21
Muse Spark 1.1won 5 · lost 19
GPT-5.4won 5 · lost 21
Qwen3.8 Maxwon 5 · lost 22
MiMo V2.6 Prowon 4 · lost 18
GLM-5.3won 3 · lost 17
Grok 4.7won 3 · lost 22
GPT-6 Solwon 3 · lost 22
Claude Opus 4.7won 3 · lost 23
Grok 4.6won 3 · lost 25
GPT-6.1 Solwon 2 · lost 18
Gemini 3 Prowon 2 · lost 18
Muse Spark 1.2won 2 · lost 18
GPT-6 Astrawon 2 · lost 19
Kimi K3won 2 · lost 20
DeepSeek V4 Prowon 2 · lost 24
GPT-5.6 Terrawon 2 · lost 24
GPT-5.5won 2 · lost 24
Claude Opus 5won 2 · lost 25
Claude Sonnet 5.5won 1 · lost 19
Claude Fable 5.1won 1 · lost 20
Claude Opus 5.5won 1 · lost 25
GPT-5.6 Solwon 1 · lost 27
Claude Fable 5won 0 · lost 20
DeepSeek V4.1 Flashwon 0 · lost 21
Claude Opus 4.8won 0 · lost 26

§ 3 · Sources

Where the numbers come from

10 publications, 49 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1439
GDPval-AA ↗1 measureread 2026-11-10
GDPval-AA 1441
AA-Briefcase ↗1 measureread 2026-11-10
AA-Briefcase 1255
ARC-AGI-2 ↗1 measureread 2026-11-10
ARC-AGI-2 61.4%
LiveBench 1.0 ↗8 measuresread 2026-11-10
LiveBench 1.0 74.2LiveBench 1.0 · Reasoning 86.6LiveBench 1.0 · Coding 75LiveBench 1.0 · Agentic Coding 46.8LiveBench 1.0 · Mathematics 86.8LiveBench 1.0 · Data Analysis 79.3LiveBench 1.0 · Language 79.2LiveBench 1.0 · Instruction Following 65.5
Kagi LLM Benchmark ↗1 measureread 2026-11-10
Kagi LLM Benchmark 52.2%
SimpleBench ↗1 measureread 2026-11-10
SimpleBench 61.1%
Vals.ai ↗15 measuresread 2026-11-10
Vals · Legal Research Bench 30.29%Vals · LegalBench 77.71%Vals · Finance Agent 49.52%Vals · CorpFin 61.85%Vals · TaxEval 70.69%Vals · MedCode 41.41%Vals · MedScribe 80.36%Vals · BioMysteryBench 64.44%Vals · CyberBench 72.08%Vals · SWE-bench Verified 88.8% (Mini-SWE-agent)Vals · Vibe Code Bench 74.74% (OpenHands)Vals · Code Migration 38.63%Vals · GPQA Diamond 89.9%Vals · MMLU Pro 86.21%Vals · ProofBench 56%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10
Enkrypt · Jailbreak risk 21%Enkrypt · Harmful content risk 23.3%Enkrypt · CBRN risk 29.7%Enkrypt · Toxicity risk 8.4%Enkrypt · Bias risk 85.3%Enkrypt · Insecure code risk 34.7%
GPQA Diamond (Pass@1) 89.9%Codeforces (Rating) 3289MathArena Apex (Pass@1) 58.6%Terminal-Bench 2.1 (Pass@1) 82.7%Terminal-Bench 3.0 (Pass@1) 7.6%Terminal-Bench 4.0 (Pass@1) 7%DeepSWE v1.1 (Resolved) 54.4%NL2Repo-Bench (Score) 54.2%CyberGym (Pass@1) 76.7%SEC-Bench Pro (Pass@1) 30.9%ExploitGym (Pass@1) 1.8%HLE w/ tools (Pass@1) 51.5%AutomationBench (Pass@1) 37.7%Agent's Last Exam (Pass@1) 25.2%

Badge

PublicAI Index badge for DeepSeek V4 Flash[![PublicAI Index](https://publicai.io/model-index/badge?model=deepseek-v4-flash)](https://publicai.io/model-index/m/deepseek-v4-flash)

✱ Placed by a one-off publication, not a board that re-ran the model. ✱✱ marks a figure the model’s own publisher printed, which counts for less again. Scores are 0–100 on the PublicAI Index scale, 50 = the average of the models each source lists. Scores belong to their publishers.

Snapshot 2026-11-10 · the full index · JSON API