Request a pilot
‹ PublicAI Index

The LLM benchmark aggregator.

DeepSeek R1

DeepSeek · 685B · open weights

Strongest in Safe-prompt compliance (#2 of 82), weakest in Safety (#285 of 337). Above par in 14 of 26 scopes. Among the models it meets almost everywhere, it finishes behind Claude Fable 5 and Claude Fable 5.1 and ahead of GPT OSS 120B and Grok 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.

Coding57.7#18/165
Code generation59#15/77
Agentic coding57#29/157
Core abilities55.7#39/204
General intelligence58.2#39/204
Knowledge52#76/138
Academic knowledge52.4#70/123
Professional48.3#98/168
Medical53.9#51/140
Finance49.1#92/151
Legal41.7#126/151
Human preference59.1#102/342
Human preference59.1#102/342
Reasoning47.1#107/178
Mathematics52#71/140
Reasoning43#95/140
Agents39.8#240/268
Knowledge work36.8#150/178
Safety45.3#285/337
Safe-prompt compliance60.4#2/82
Fairness55.1#67/300
Factual grounding46.7#71/101
Toxicity avoidance56#77/272
Jailbreak resistance32.9#247/272
Secure code30.2#251/274
Harm refusal41.4#281/300

§ 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 R1, left for the other.

GPT-4.1 Nanowon 19 · lost 5
Gemini 2.0 Flashwon 17 · lost 5
DeepSeek V3won 20 · lost 6
Grok Build 0.1won 12 · lost 4
Gemini 1.5 Flashwon 12 · lost 4
Mistral Medium 3.5won 12 · lost 4
Gemini 1.5 Prowon 13 · lost 5
GPT-4o Miniwon 17 · lost 7
Kimi K2won 17 · lost 7
Command R Pluswon 12 · lost 5
Grok 3won 14 · lost 6
Llama 4 Scout Instructwon 16 · lost 7
O3 Miniwon 16 · lost 7
Mistral Smallwon 13 · lost 6
Mistral Large 3won 13 · lost 6
Command Awon 15 · lost 7
Gemini 2.5 Flash Litewon 12 · lost 6
GPT-5.4 Nanowon 13 · lost 7
Ling 3.0 Flashwon 11 · lost 6
Grok 4 Fastwon 11 · lost 6
GPT-4.1 Miniwon 15 · lost 9
GPT-4owon 13 · lost 9
GPT-5 Nanowon 13 · lost 9
Mistral Largewon 10 · lost 7
GPT-4.1won 14 · lost 10
GPT OSS 20Bwon 12 · lost 9
Kimi K2.7 Codewon 9 · lost 7
GPT-4 Turbowon 9 · lost 7
Claude 3.5 Haikuwon 10 · lost 9
GPT-5.4 Miniwon 10 · lost 9
Claude 3.7 Sonnetwon 11 · lost 10
Grok 4won 12 · lost 11
GPT OSS 120Bwon 13 · lost 12
Qwen3.6 Pluswon 9 · lost 9
Gemini 3.5 Flash Litewon 9 · lost 9
Claude 3.5 Sonnetwon 10 · lost 10
Grok 4.3won 12 · lost 12
O4 Miniwon 12 · lost 13
Claude Haiku 4.5won 12 · lost 13
MiniMax M2.7won 9 · lost 11
GLM-4.5won 8 · lost 10
Gemini 2.5 Flashwon 11 · lost 14
Grok 4.1 Fastwon 9 · lost 12
Gemma 4 31Bwon 9 · lost 12
Qwen3 235B A22B Instructwon 10 · lost 14
MiniMax M3won 10 · lost 14
GLM-5.2won 10 · lost 14
O1won 8 · lost 12
GLM-4.6won 9 · lost 14
Gemini 3.1 Flash Litewon 7 · lost 11
Qwen3.8 27Bwon 7 · lost 11
DeepSeek V4 Flashwon 9 · lost 15
GLM-5.3 Flashwon 9 · lost 15
Qwen3.7 Maxwon 9 · lost 15
Gemini 3.5 Flashwon 9 · lost 15
Gemini 3.6 Flashwon 9 · lost 15
Kimi K2 Thinkingwon 7 · lost 12
Mimo V2.5 Prowon 8 · lost 14
GPT-5 Miniwon 9 · lost 16
Kimi K2.6won 9 · lost 16
DeepSeek V3.2won 8 · lost 16
Inklingwon 8 · lost 16
GPT-5.6 Lunawon 8 · lost 16
GPT-6 Lunawon 7 · lost 15
Claude Sonnet 4won 8 · lost 18
Muse Spark 1.1won 7 · lost 17
Claude Opus 4.6won 6 · lost 15
GPT-5.4won 7 · lost 18
Muse Spark 1.2won 5 · lost 13
Claude Opus 4.5won 5 · lost 14
Claude Sonnet 4.6won 6 · lost 17
Gemini 3.1 Prowon 5 · lost 15
Claude Opus 4won 6 · lost 18
GPT-5.2won 6 · lost 18
Kimi K2.5won 6 · lost 18
Claude Sonnet 5won 6 · lost 18
GPT-5.6 Terrawon 6 · lost 18
Gemini 3.8 Flashwon 6 · lost 18
Claude Sonnet 4.5won 6 · lost 19
DeepSeek V4 Prowon 6 · lost 19
GLM-5.1won 5 · lost 16
Gemini 3.7 Flashwon 4 · lost 14
GPT-5.1won 5 · lost 18
O3won 5 · lost 19
Grok 4.5won 5 · lost 19
Qwen3.8 Maxwon 5 · lost 19
GPT-5won 5 · lost 20
Claude Opus 4.7won 5 · lost 20
Gemini 2.5 Prowon 5 · lost 21
Gemini 3 Prowon 4 · lost 17
DeepSeek V4.1 Flashwon 3 · lost 14
GLM-5.3won 3 · lost 15
Grok 4.7won 3 · lost 19
Grok 4.6won 3 · lost 21
Claude Opus 5won 3 · lost 21
GPT-5.6 Solwon 3 · lost 22
GLM-5won 2 · lost 15
Kimi K3won 2 · lost 16
Mimo V2.6 Prowon 2 · lost 17
GPT-6 Solwon 2 · lost 21
Claude Opus 4.8won 2 · lost 22
GPT-5.5won 2 · lost 23
GPT-6 Astrawon 1 · lost 17
Claude Opus 5.5won 1 · lost 21
Claude Fable 5.1won 0 · lost 18
Claude Fable 5won 0 · lost 18

§ 3 · Sources

Where the numbers come from

12 publications, 26 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-09-26
LMArena Text 1422
GDPval-AA ↗1 measureread 2026-09-26
GDPval-AA 282
AA-Briefcase ↗1 measureread 2026-09-26
AA-Briefcase 130
ARC-AGI-2 ↗1 measureread 2026-09-26
ARC-AGI-2 1.1%
LiveCodeBench ↗1 measureread 2026-09-26
LiveCodeBench 73.1%
Aider polyglot ↗1 measureread 2026-09-26
Aider polyglot 71.4%
Kagi LLM Benchmark ↗1 measureread 2026-09-26
Kagi LLM Benchmark 69.4%
SimpleBench ↗1 measureread 2026-09-26
SimpleBench 40.8%
Vals.ai ↗6 measuresread 2026-09-26
Vals · LegalBench 67.32%Vals · CorpFin 54.12%Vals · TaxEval 72.28%Vals · MedQA 90.8%Vals · MMLU Pro 83.18%Vals · AIME 73.96%
HELM Safety ↗5 measuresread 2026-09-26
HELM Safety · HarmBench 54.6%HELM Safety · SimpleSafetyTests 98.3%HELM Safety · Anthropic Red Team 99.1%HELM Safety · BBQ 96.5%HELM Safety · XSTest 98.8%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-09-26
Enkrypt · Jailbreak risk 27.2%Enkrypt · Harmful content risk 57.8%Enkrypt · CBRN risk 53.5%Enkrypt · Toxicity risk 2.1%Enkrypt · Bias risk 74.9%Enkrypt · Insecure code risk 73.8%
Vectara · Factual consistency 88.7%

Badge

PublicAI Index badge for DeepSeek R1[![PublicAI Index](https://publicai.io/model-index/badge?model=deepseek-r1)](https://publicai.io/model-index/m/deepseek-r1)