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GPT-5.6 Luna

OpenAI

Strongest in Cybersecurity (#11 of 47), weakest in Toxicity avoidance (#196 of 268). Above par in 28 of 37 scopes. Among the models it meets almost everywhere, it finishes behind Claude Fable 5.1 and GPT-5.6 Sol and ahead of GLM-5.3 Flash and GPT-5 mini.

§ 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.

Agents57#35/298
Knowledge work61.2#39/208
Tool use57.1—/81✱
Web research55.3—/35✱
Workflow automation55.9—/0✱
Knowledge55.1#39/197
Document parsing55.1#35/83
Academic knowledge56#49/123
Factuality50.7—/0✱
Coding54.4#44/179
Agentic coding54.6#42/173
Code generation63.8—/20✱
Human preference61.8#63/354
Human preference61.8#63/354
Professional52.7#64/194
Cybersecurity57.8#11/47
Finance57.7#22/162
IT operations40.2#28/33
Biology research38#28/31
Legal54.3#51/173
Medical52.7#66/149
Safety53.7#78/329
Secure code62.3#40/270
Harm refusal54.1#86/292
Fairness49.9#117/292
Jailbreak resistance53.8#131/268
Toxicity avoidance50#196/268
Reasoning51.7#86/195
Science60.9#19/122
Reasoning50.4#63/147
Mathematics48.4#93/152
Expert reasoning62—/0✱
Core abilities43.4#161/199
Language42.8#52/62
Instruction following36#54/62
General intelligence48.2#105/178
Long context62.2—/0✱

§ 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-5.6 Luna, left for the other.

GPT-4.1 nanowon 22 · lost 2
GPT-4.1 miniwon 22 · lost 2
GPT-4o miniwon 21 · lost 2
DeepSeek V3won 21 · lost 3
Gemini 2.5 Flashwon 20 · lost 3
Grok 4.3won 20 · lost 4
MiniMax M3won 22 · lost 5
DeepSeek V3.2won 18 · lost 6
Kimi K2.5won 18 · lost 6
Claude Haiku 4.5won 17 · lost 6
Kimi K2won 17 · lost 6
GLM-4.6won 17 · lost 6
DeepSeek V4 Flashwon 20 · lost 8
GPT OSS 120Bwon 17 · lost 7
Mistral Large 4won 17 · lost 7
Claude Sonnet 4won 16 · lost 8
Kimi K2.6won 16 · lost 8
O4 Miniwon 15 · lost 8
Grok 4won 15 · lost 8
DeepSeek R1won 15 · lost 8
GPT-6 Lunawon 18 · lost 10
Gemini 2.5 Prowon 15 · lost 9
Qwen3 235B A22B Instructwon 14 · lost 9
Qwen3.7 Maxwon 15 · lost 10
Inklingwon 16 · lost 11
GLM-5.2won 15 · lost 11
GPT-4.1won 13 · lost 10
Gemini 3.6 Flashwon 15 · lost 13
MiMo V2.6 Flashwon 12 · lost 11
GPT-5 miniwon 13 · lost 12
GLM-5.3 Flashwon 15 · lost 14
DeepSeek V4 Prowon 13 · lost 15
O3won 10 · lost 13
Claude Sonnet 4.6won 10 · lost 13
MiMo V2.6 Prowon 10 · lost 13
Gemini 3.5 Flashwon 11 · lost 15
GPT-5won 10 · lost 14
Grok 4.5won 11 · lost 17
Claude Sonnet 4.5won 9 · lost 15
GPT-5.4won 10 · lost 17
Qwen3.8 Maxwon 10 · lost 17
Gemini 3.8 Flashwon 10 · lost 20
Claude Opus 4.6won 7 · lost 16
GPT-5.2won 7 · lost 18
DeepSeek V4.1 Flashwon 6 · lost 17
GPT-6 Solwon 7 · lost 20
Claude Opus 4.7won 7 · lost 20
Muse Spark 1.1won 6 · lost 18
Claude Sonnet 5won 7 · lost 21
Grok 4.7won 6 · lost 20
GPT-5.6 Terrawon 6 · lost 23
Claude Opus 4.8won 5 · lost 22
Grok 4.6won 5 · lost 23
GPT-6 Astrawon 4 · lost 19
GPT-5.5won 3 · lost 25
Claude Opus 5won 3 · lost 25
Claude Opus 5.5won 3 · lost 25
GPT-5.6 Solwon 3 · lost 27
Claude Fable 5.1won 1 · lost 22

§ 3 · Sources

Where the numbers come from

12 publications, 61 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1453
GDPval-AA ↗1 measureread 2026-11-10
GDPval-AA 1468
AA-Briefcase ↗1 measureread 2026-11-10
AA-Briefcase 1339
Terminal-Bench ↗1 measureread 2026-11-10
Terminal-Bench 17.6% (Codex)
ARC-AGI-2 ↗1 measureread 2026-11-10
ARC-AGI-2 59.6%
LiveBench 1.0 ↗8 measuresread 2026-11-10
LiveBench 1.0 73.6LiveBench 1.0 · Reasoning 85.6LiveBench 1.0 · Coding 82.9LiveBench 1.0 · Agentic Coding 48.4LiveBench 1.0 · Mathematics 87.2LiveBench 1.0 · Data Analysis 78LiveBench 1.0 · Language 72.6LiveBench 1.0 · Instruction Following 60.1
Kagi LLM Benchmark ↗1 measureread 2026-11-10
Kagi LLM Benchmark 49.1%
SimpleBench ↗1 measureread 2026-11-10
SimpleBench 46.8%
Vals.ai ↗17 measuresread 2026-11-10
Vals · Legal Research Bench 36.54%Vals · LegalBench 84.03%Vals · Finance Agent 55.04%Vals · CorpFin 64.22%Vals · TaxEval 76.17%Vals · MortgageTax 67.29%Vals · MedCode 42.39%Vals · MedScribe 84.39%Vals · BioMysteryBench 61.48%Vals · CyberBench 73.63%Vals · SRE Bench 1.53%Vals · SWE-bench Verified 93% (Mini-SWE-agent)Vals · Vibe Code Bench 77.06% (OpenHands)Vals · Code Migration 44.55%Vals · GPQA Diamond 91.67%Vals · MMLU Pro 86.04%Vals · ProofBench 60%
ParseBench ↗6 measuresread 2026-11-10
ParseBench · Overall 66.73%ParseBench · Tables 88.3%ParseBench · Charts 49.16%ParseBench · Content faithfulness 86.4%ParseBench · Semantic formatting 64.95%ParseBench · Visual grounding 44.83%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10
Enkrypt · Jailbreak risk 9.6%Enkrypt · Harmful content risk 0%Enkrypt · CBRN risk 22.2%Enkrypt · Toxicity risk 6.2%Enkrypt · Bias risk 78%Enkrypt · Insecure code risk 8%
GDPVal-AA 1569tau3-Banking 31.1%Toolathlon Verified 67.5%Automation Bench Public 33.5%Apex-Agents (pass@1) 28.6%MCPMark 66.9%BrowseComp 83.3%WildClawBench 50.4%Terminal-Bench 2.1 80.9%SciCode 52.5%SWE Bench Pro 48.8%Humanity's Last Exam (without tools) 39.5%GPQA Diamond 91.1%CritPt 21%AA-LCR 78.3%AA-Omniscience Accuracy 43%AA-Omniscience Non-Hallucination 7%

Badge

PublicAI Index badge for GPT-5.6 Luna[![PublicAI Index](https://publicai.io/model-index/badge?model=gpt-5-6-luna)](https://publicai.io/model-index/m/gpt-5-6-luna)

✱ 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