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The LLM benchmark aggregator.

GPT-5

OpenAI

Strongest in Secure code (#10 of 270), weakest in Agents (#116 of 298). Above par in 24 of 26 scopes. Among the models it meets almost everywhere, it finishes behind Claude Fable 5 and Claude Fable 5.1 and ahead of Gemini 3.6 Flash and Gemini 3.5 Flash.

§ 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.

Safety58.7#11/329
Secure code65.2#10/270
Harm refusal59.3#15/292
Jailbreak resistance62.8#17/268
Fairness66.2#19/292
Safe-prompt compliance56.6#23/82
Factual grounding36.9#94/104
Toxicity avoidance54.8#110/268
Professional56.4#21/194
Legal59.2#16/173
Medical58.1#20/149
Finance54.2#59/162
Core abilities56.8#31/199
General intelligence59.8#28/178
Reasoning53.1#65/195
Mathematics57.2#28/152
Science56.6#46/122
Reasoning47.9#76/147
Knowledge52.8#71/197
Academic knowledge56.6#40/123
Coding51.7#76/179
Agentic coding51.8#73/173
Human preference60#87/354
Human preference60#87/354
Agents50.8#116/298
Knowledge work51.5#87/208

§ 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 GPT-5, left for the other.

Magistral Small 1.2won 17 · lost 0
Gemini 1.5 Flashwon 17 · lost 0
Mistral Medium 3.5won 17 · lost 0
Grok 4 Fastwon 18 · lost 0
Kimi K2 Thinkingwon 19 · lost 0
GLM-4.5won 19 · lost 0
GPT OSS 20Bwon 22 · lost 0
Gemini 2.0 Flashwon 23 · lost 0
GPT-4.1 nanowon 25 · lost 0
GPT-4.1 miniwon 24 · lost 1
GPT-4o miniwon 23 · lost 1
GPT-5.4 nanowon 19 · lost 1
Mistral Large 3won 19 · lost 1
Gemini 1.5 Prowon 18 · lost 1
Ling 3.0 Flashwon 17 · lost 1
Command R+won 17 · lost 1
MiniMax M2.5won 17 · lost 1
DeepSeek V3.1won 15 · lost 1
GPT OSS 120Bwon 24 · lost 2
DeepSeek V3won 23 · lost 2
DeepSeek V3.2won 23 · lost 2
Llama 4 Scout Instructwon 22 · lost 2
GLM-4.6won 22 · lost 2
Command Awon 21 · lost 2
O3 Miniwon 21 · lost 2
Llama 3.3 70B Instructwon 18 · lost 2
Grok 3 Miniwon 18 · lost 2
Gemini 2.5 Flash-Litewon 17 · lost 2
Gemini 3.1 Flash-Litewon 17 · lost 2
Gemini 3.5 Flash-Litewon 16 · lost 2
Grok 3won 21 · lost 3
Claude Haiku 4.5won 21 · lost 3
Grok 4.1 Fastwon 19 · lost 3
Grok 4.3won 19 · lost 3
GPT-5 miniwon 22 · lost 4
GPT-5.4 miniwon 16 · lost 3
O4 Miniwon 21 · lost 4
Kimi K2won 21 · lost 4
GPT-4owon 20 · lost 4
MiniMax M2.1won 13 · lost 3
Gemma 4 31Bwon 17 · lost 4
Claude 3.5 Haikuwon 16 · lost 4
Gemini 2.5 Flashwon 20 · lost 5
DeepSeek R1won 20 · lost 5
Qwen3 235B A22B Instructwon 20 · lost 5
O3won 19 · lost 5
Inkling Smallwon 14 · lost 4
Claude 3.7 Sonnetwon 17 · lost 5
Claude Sonnet 4won 20 · lost 6
Gemini 2.5 Prowon 20 · lost 6
O1won 16 · lost 5
MiMo V2.5 Prowon 16 · lost 5
Mistral Large 4won 15 · lost 5
Grok 4won 18 · lost 6
Claude Sonnet 4.5won 19 · lost 7
MiniMax M2.7won 16 · lost 6
GLM-5won 13 · lost 5
GPT-4.1won 18 · lost 7
Kimi K2.5won 18 · lost 7
MiniMax M3won 17 · lost 7
Claude 3.5 Sonnetwon 14 · lost 6
GPT-5 nanowon 16 · lost 7
Inklingwon 16 · lost 7
GPT-6 Lunawon 15 · lost 7
Qwen3.8 27Bwon 12 · lost 6
GLM-4.7won 12 · lost 6
Claude Opus 4won 16 · lost 8
DeepSeek V4 Flashwon 16 · lost 8
Kimi K2.6won 15 · lost 8
MiMo V2.6 Flashwon 13 · lost 7
GLM-5.1won 14 · lost 8
GLM-5.3 Flashwon 15 · lost 9
MiMo V2.6 Prowon 13 · lost 8
GPT-5.6 Lunawon 14 · lost 10
GPT-5.1won 14 · lost 10
Qwen3.7 Maxwon 13 · lost 10
Qwen3.6 Pluswon 9 · lost 7
Claude Sonnet 4.6won 12 · lost 10
GLM-5.2won 13 · lost 11
Gemini 3.8 Flashwon 13 · lost 11
Gemini 3.5 Flashwon 12 · lost 11
Gemini 3.6 Flashwon 12 · lost 11
Claude Haiku 5.5won 8 · lost 8
Grok 4.20won 8 · lost 8
GPT-6 Solwon 11 · lost 11
GPT-5.2won 12 · lost 12
Qwen3.8 Maxwon 12 · lost 12
DeepSeek V4 Prowon 12 · lost 13
Grok 4.7won 10 · lost 11
Claude Opus 4.6won 10 · lost 11
Gemini 3.1 Prowon 9 · lost 10
GPT-5.6 Terrawon 11 · lost 13
Grok 4.6won 10 · lost 14
Grok 4.5won 10 · lost 14
GPT-5.4won 10 · lost 15
DeepSeek V4.1 Flashwon 7 · lost 11
GLM-5.3won 7 · lost 11
Gemini 3 Flashwon 6 · lost 10
Gemini 3 Prowon 8 · lost 14
GPT-5.5won 8 · lost 17
GPT-5.6 Solwon 8 · lost 17
Muse Spark 1.1won 7 · lost 15
Claude Opus 4.5won 6 · lost 13
GPT-6 Astrawon 5 · lost 13
Claude Sonnet 5won 6 · lost 17
GPT-6.1 Solwon 4 · lost 12
Muse Spark 1.2won 4 · lost 12
Kimi K3won 4 · lost 14
Claude Opus 4.8won 5 · lost 19
Gemini 3.7 Flashwon 3 · lost 14
Claude Opus 5won 4 · lost 19
Claude Opus 5.5won 4 · lost 19
Claude Opus 4.7won 4 · lost 21
Claude Sonnet 5.5won 2 · lost 14
Gemini 4 Argonwon 1 · lost 16
Claude Fable 5.1won 0 · lost 18
Claude Fable 5won 0 · lost 18

§ 3 · Sources

Where the numbers come from

10 publications, 31 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1435
GDPval-AA ↗1 measureread 2026-11-10
GDPval-AA 925
ARC-AGI-2 ↗1 measureread 2026-11-10
ARC-AGI-2 9.9%
Aider polyglot ↗1 measureread 2026-11-10
Aider polyglot 88%
Kagi LLM Benchmark ↗1 measureread 2026-11-10
Kagi LLM Benchmark 72.7%
SimpleBench ↗1 measureread 2026-11-10
SimpleBench 56.7%
Vals.ai ↗13 measuresread 2026-11-10
Vals · CaseLaw 66.45%Vals · LegalBench 86.02%Vals · CorpFin 61.07%Vals · TaxEval 73.39%Vals · MortgageTax 65.45%Vals · MedQA 96.32%Vals · MedCode 49.63%Vals · MedScribe 83.65%Vals · SWE-bench Verified 69% (Mini-SWE-agent)Vals · Vibe Code Bench 20.09% (OpenHands)Vals · GPQA Diamond 85.61%Vals · MMLU Pro 86.54%Vals · AIME 93.37%
HELM Safety ↗5 measuresread 2026-11-10
HELM Safety · HarmBench 97.6%HELM Safety · SimpleSafetyTests 99.8%HELM Safety · Anthropic Red Team 99.1%HELM Safety · BBQ 96.8%HELM Safety · XSTest 97.1%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10
Enkrypt · Jailbreak risk 2.1%Enkrypt · Harmful content risk 6.7%Enkrypt · CBRN risk 7.1%Enkrypt · Toxicity risk 2.9%Enkrypt · Bias risk 40.1%Enkrypt · Insecure code risk 2.2%
Vectara · Factual consistency 84.9%

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