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GPT-5 Mini

OpenAI

Strongest in Harm refusal (#11 of 300), weakest in Toxicity avoidance (#176 of 272). Above par in 22 of 27 scopes. Among the models it meets almost everywhere, it finishes behind Claude Fable 5 and Claude Fable 5.1 and ahead of GLM-5.2 and GPT-5.6 Luna.

§ 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.

Safety58.4#15/337
Harm refusal59.8#11/300
Secure code65#13/274
Safe-prompt compliance57.9#15/82
Jailbreak resistance62.1#22/272
Fairness61.2#35/300
Factual grounding42.6#83/101
Toxicity avoidance52.1#176/272
Professional55.4#32/168
Legal58.4#20/151
Finance55.1#45/151
Medical54.5#47/140
Core abilities56#35/204
General intelligence58.6#35/204
Reasoning51.7#78/178
Mathematics56.7#33/140
Science52.9#67/122
Reasoning43.6#88/140
Knowledge51#80/138
Academic knowledge51.3#74/123
Agents51#108/268
Tool use62.8#14/81
Knowledge work45.3#105/178
Coding43.1#133/165
Agentic coding42#128/157
Human preference56#134/342
Human preference56#134/342

§ 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 Mini, left for the other.

Gemini 1.5 Flashwon 17 · lost 0
GPT OSS 20Bwon 22 · lost 0
GPT-4.1 Nanowon 25 · lost 1
GPT-4o Miniwon 23 · lost 1
Mistral Smallwon 20 · lost 1
Command R Pluswon 17 · lost 1
GPT-4.1 Miniwon 24 · lost 2
Llama 4 Scout Instructwon 23 · lost 2
Gemini 2.0 Flashwon 21 · lost 2
Gemini 2.5 Flash Litewon 18 · lost 2
Mistral Large 3won 18 · lost 2
Mistral Largewon 17 · lost 2
Gemini 1.5 Prowon 17 · lost 2
Command Awon 21 · lost 3
Grok 3won 18 · lost 3
GPT OSS 120Bwon 22 · lost 4
GLM-4.5won 16 · lost 3
O3 Miniwon 19 · lost 4
Mistral Medium 3.5won 14 · lost 3
GPT-4owon 18 · lost 4
O4 Miniwon 21 · lost 5
DeepSeek V3won 21 · lost 5
Ling 3.0 Flashwon 14 · lost 4
Kimi K2 Thinkingwon 15 · lost 5
Grok 4.3won 18 · lost 6
Claude Haiku 4.5won 20 · lost 7
Kimi K2won 19 · lost 7
Gemma 4 31Bwon 16 · lost 6
Grok 4 Fastwon 13 · lost 5
Qwen3 235B A22B Instructwon 18 · lost 7
GPT-5 Nanowon 17 · lost 7
GPT-5.4 Nanowon 14 · lost 6
Claude 3.7 Sonnetwon 15 · lost 7
GPT-6 Lunawon 14 · lost 7
Claude 3.5 Haikuwon 13 · lost 7
DeepSeek R1won 16 · lost 9
Gemini 3.1 Flash Litewon 12 · lost 7
Gemini 2.5 Flashwon 16 · lost 10
GPT-4.1won 16 · lost 10
DeepSeek V3.2won 15 · lost 11
Grok 4.1 Fastwon 13 · lost 10
Mimo V2.5 Prowon 13 · lost 10
GLM-4.6won 14 · lost 11
MiniMax M3won 14 · lost 11
Gemini 3.5 Flash Litewon 10 · lost 8
Claude 3.5 Sonnetwon 11 · lost 9
DeepSeek V4 Flashwon 13 · lost 11
O1won 11 · lost 10
GPT-5.6 Lunawon 13 · lost 12
GLM-5.2won 13 · lost 12
Qwen3.6 Pluswon 9 · lost 9
Qwen3.7 Maxwon 12 · lost 12
Claude Sonnet 4won 13 · lost 13
O3won 12 · lost 13
Kimi K2.6won 12 · lost 13
DeepSeek V4 Prowon 12 · lost 13
GPT-5.6 Terrawon 12 · lost 13
GPT-5.4 Miniwon 9 · lost 10
Gemini 2.5 Prowon 12 · lost 14
Grok 4won 11 · lost 14
Qwen3.8 27Bwon 8 · lost 11
Claude Opus 4won 10 · lost 14
GLM-5.3 Flashwon 10 · lost 14
Gemini 3.6 Flashwon 10 · lost 14
DeepSeek V4.1 Flashwon 7 · lost 10
GPT-6 Solwon 9 · lost 13
GLM-5.1won 9 · lost 13
Claude Sonnet 4.5won 11 · lost 16
Inklingwon 10 · lost 15
Kimi K2.5won 10 · lost 15
MiniMax M2.7won 8 · lost 13
Gemini 3.5 Flashwon 9 · lost 15
GPT-5.4won 9 · lost 16
Gemini 3.1 Prowon 7 · lost 13
Claude Sonnet 4.6won 8 · lost 15
Claude Opus 4.6won 7 · lost 14
Grok 4.5won 8 · lost 16
Qwen3.8 Maxwon 8 · lost 16
Gemini 3.8 Flashwon 8 · lost 16
Mimo V2.6 Prowon 6 · lost 13
Gemini 3 Prowon 7 · lost 16
Claude Sonnet 5won 7 · lost 18
GPT-5.5won 7 · lost 18
GPT-5.6 Solwon 7 · lost 18
Claude Opus 4.5won 5 · lost 15
GPT-5.1won 6 · lost 18
GPT-5.2won 6 · lost 19
Grok 4.7won 5 · lost 16
GLM-5won 4 · lost 14
Claude Opus 4.8won 5 · lost 19
Claude Opus 5won 5 · lost 19
GPT-6 Astrawon 3 · lost 14
Muse Spark 1.2won 3 · lost 14
Gemini 3.7 Flashwon 3 · lost 15
Grok 4.6won 4 · lost 20
Muse Spark 1.1won 4 · lost 20
Claude Opus 4.7won 4 · lost 21
GPT-5won 4 · lost 22
Claude Opus 5.5won 3 · lost 18
GLM-5.3won 2 · lost 16
Kimi K3won 1 · lost 17
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 2026-09-26
LMArena Text 1390
GDPval-AA ↗1 measureread 2026-09-26
GDPval-AA 754
AA-Briefcase ↗1 measureread 2026-09-26
AA-Briefcase 428
ARC-AGI-2 ↗1 measureread 2026-09-26
ARC-AGI-2 4.4%
BFCL ↗1 measureread 2026-09-26
BFCL v4 55.46%
Kagi LLM Benchmark ↗1 measureread 2026-09-26
Kagi LLM Benchmark 70.3%
Vals.ai ↗13 measuresread 2026-09-26
Vals · CaseLaw 68.49%Vals · LegalBench 81.77%Vals · CorpFin 60.18%Vals · TaxEval 75.22%Vals · MortgageTax 66.89%Vals · MedQA 96.06%Vals · MedCode 43.05%Vals · MedScribe 80.58%Vals · SWE-bench Verified 60.8% (Mini-SWE-agent)Vals · Vibe Code Bench 14.17% (OpenHands)Vals · GPQA Diamond 80.3%Vals · MMLU Pro 82.23%Vals · AIME 91.46%
HELM Safety ↗5 measuresread 2026-09-26
HELM Safety · HarmBench 97.1%HELM Safety · SimpleSafetyTests 100%HELM Safety · Anthropic Red Team 99.1%HELM Safety · BBQ 96.3%HELM Safety · XSTest 97.7%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-09-26
Enkrypt · Jailbreak risk 2.6%Enkrypt · Harmful content risk 8.9%Enkrypt · CBRN risk 3.2%Enkrypt · Toxicity risk 4.8%Enkrypt · Bias risk 58.9%Enkrypt · Insecure code risk 3.1%
Vectara · Factual consistency 87.1%

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