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GPT-6 Sol

OpenAI

Strongest in Cybersecurity (#2 of 47), weakest in Toxicity avoidance (#222 of 268). Above par in 26 of 28 scopes. Among the models it meets almost everywhere, it finishes behind Claude Fable 5 and Claude Fable 5.1 and ahead of Gemini 3.8 Flash and Claude Opus 4.7.

§ 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.

Reasoning60.5#12/195
Mathematics60.2#12/152
Reasoning62#15/147
Coding58.3#18/179
Agentic coding58.7#17/173
Agents58.3#26/298
Knowledge work63.3#32/208
Knowledge56.3#30/197
Document parsing56.7#28/83
Professional54.5#36/194
Cybersecurity61.8#2/47
IT operations62.1#6/33
Biology research57.6#9/31
Medical54.4#50/149
Finance50.9#93/162
Legal48.3#103/173
Human preference62.1#56/354
Human preference62.1#56/354
Core abilities53.8#59/199
Language59.5#13/62
Instruction following51.1#32/62
Safety52.4#117/329
Factual grounding58.7#29/104
Fairness54#77/292
Secure code57.3#92/270
Harm refusal50.5#145/292
Jailbreak resistance50.7#173/268
Toxicity avoidance46.3#222/268

§ 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 GPT-6 Sol, left for the other.

Gemini 3.5 Flash-Litewon 18 · lost 1
Mistral Large 3won 16 · lost 1
Gemini 3.1 Flash-Litewon 16 · lost 1
DeepSeek V3won 20 · lost 2
Grok 4.3won 20 · lost 2
Gemma 4 31Bwon 19 · lost 2
Llama 4 Scout Instructwon 18 · lost 2
GPT-5.4 nanowon 18 · lost 2
Grok 4.1 Fastwon 18 · lost 2
DeepSeek V4 Flashwon 22 · lost 3
DeepSeek R1won 19 · lost 3
DeepSeek V3.2won 18 · lost 3
GLM-4.6won 18 · lost 3
Command Awon 17 · lost 3
Grok 3won 17 · lost 3
Grok 4won 17 · lost 3
Qwen3.8 27Bwon 16 · lost 3
GPT OSS 20Bwon 15 · lost 3
GPT-5.4 miniwon 15 · lost 3
Kimi K2.5won 18 · lost 4
GPT-6 Lunawon 22 · lost 5
Kimi K2won 17 · lost 4
Claude Haiku 5.5won 17 · lost 4
GPT-4o miniwon 16 · lost 4
MiniMax M3won 19 · lost 5
Gemini 2.0 Flashwon 15 · lost 4
Mistral Large 4won 18 · lost 5
GPT OSS 120Bwon 17 · lost 5
Claude Haiku 4.5won 17 · lost 5
MiMo V2.6 Flashwon 17 · lost 5
GPT-4.1 nanowon 16 · lost 5
Gemini 2.5 Flashwon 16 · lost 5
GPT-5.6 Lunawon 20 · lost 7
GLM-5.2won 17 · lost 6
Gemini 2.5 Prowon 16 · lost 6
Llama 3.3 70B Instructwon 13 · lost 5
Claude 3.5 Haikuwon 13 · lost 5
GPT-4owon 15 · lost 6
Qwen3 235B A22B Instructwon 15 · lost 6
Claude 3.5 Sonnetwon 12 · lost 5
O3 Miniwon 14 · lost 6
MiniMax M2.7won 14 · lost 6
Kimi K2.6won 16 · lost 7
GPT-5 nanowon 13 · lost 6
Claude 3.7 Sonnetwon 13 · lost 6
MiMo V2.5 Prowon 13 · lost 6
Claude Sonnet 4.6won 15 · lost 7
GPT-4.1 miniwon 14 · lost 7
Inklingwon 16 · lost 8
DeepSeek V4 Prowon 17 · lost 9
Qwen3.7 Maxwon 15 · lost 8
Claude Sonnet 4won 14 · lost 8
Claude Sonnet 4.5won 14 · lost 8
Claude Opus 4.6won 13 · lost 8
Claude Sonnet 5won 16 · lost 10
GPT-5.6 Terrawon 16 · lost 10
GLM-5.3 Flashwon 16 · lost 10
Gemini 3.6 Flashwon 16 · lost 10
Claude Opus 4.5won 11 · lost 7
Claude Opus 4won 12 · lost 8
GLM-5.1won 12 · lost 8
MiMo V2.6 Prowon 13 · lost 9
Kimi K2 Thinkingwon 10 · lost 7
Muse Spark 1.3won 10 · lost 7
Muse Spark 1.2won 11 · lost 8
O4 Miniwon 12 · lost 9
GPT-4.1won 12 · lost 9
GPT-5 miniwon 13 · lost 10
GPT-5.2won 13 · lost 10
O1won 10 · lost 8
Gemini 3 Prowon 10 · lost 8
GPT-5.1won 11 · lost 10
Gemini 3.1 Prowon 11 · lost 10
DeepSeek V4.1 Flashwon 12 · lost 11
Grok 4.6won 13 · lost 12
GPT-5.4won 13 · lost 12
Claude Opus 4.7won 13 · lost 12
Gemini 3.8 Flashwon 14 · lost 13
Gemini 3.7 Flashwon 10 · lost 10
GPT-5won 11 · lost 11
Gemini 3.5 Flashwon 12 · lost 12
Qwen3.8 Maxwon 12 · lost 12
Grok 4.7won 12 · lost 13
Grok 4.5won 12 · lost 13
Kimi K3won 9 · lost 10
Claude Opus 4.8won 11 · lost 13
Muse Spark 1.1won 10 · lost 12
GPT-5.5won 11 · lost 15
GLM-5.3won 8 · lost 11
O3won 8 · lost 12
GPT-5.6 Solwon 9 · lost 18
Claude Sonnet 5.5won 5 · lost 16
Muse Wonderwon 4 · lost 13
Claude Opus 5won 5 · lost 21
Gemini 4 Argonwon 3 · lost 16
GPT-6.1 Solwon 3 · lost 18
GPT-6 Astrawon 3 · lost 20
Claude Opus 5.5won 3 · lost 25
Claude Fable 5.1won 2 · lost 18
Claude Fable 5won 1 · lost 17

§ 3 · Sources

Where the numbers come from

11 publications, 37 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1457
GDPval-AA ↗1 measureread 2026-11-10
GDPval-AA 1516
AA-Briefcase ↗1 measureread 2026-11-10
AA-Briefcase 1476
Terminal-Bench ↗1 measureread 2026-11-10
Terminal-Bench 50.3% (Codex)
ARC-AGI-2 ↗1 measureread 2026-11-10
ARC-AGI-2 89.6%
LiveBench 1.0 ↗8 measuresread 2026-11-10
LiveBench 1.0 79.3LiveBench 1.0 · Reasoning 88.7LiveBench 1.0 · Coding 81.8LiveBench 1.0 · Agentic Coding 52.9LiveBench 1.0 · Mathematics 96.4LiveBench 1.0 · Data Analysis 81.2LiveBench 1.0 · Language 85.3LiveBench 1.0 · Instruction Following 68.6
SimpleBench ↗1 measureread 2026-11-10
SimpleBench 73.1%
Vals.ai ↗10 measuresread 2026-11-10
Vals · Legal Research Bench 28.85%Vals · Finance Agent 49.05%Vals · MedCode 47.07%Vals · MedScribe 82.03%Vals · BioMysteryBench 74.81%Vals · CyberBench 77.98%Vals · SRE Bench 30.53%Vals · Vibe Code Bench 87.82% (OpenHands)Vals · Code Migration 57.2%Vals · ProofBench 83%
ParseBench ↗6 measuresread 2026-11-10
ParseBench · Overall 68.85%ParseBench · Tables 92.65%ParseBench · Charts 48.05%ParseBench · Content faithfulness 87.54%ParseBench · Semantic formatting 67.91%ParseBench · Visual grounding 48.12%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10
Enkrypt · Jailbreak risk 12.2%Enkrypt · Harmful content risk 0%Enkrypt · CBRN risk 31.8%Enkrypt · Toxicity risk 8.7%Enkrypt · Bias risk 71.6%Enkrypt · Insecure code risk 18.2%
Vectara · Factual consistency 93.5%

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