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GLM-5.2

Z.ai · 753B · open weights

Strongest in Human preference (#30 of 354), weakest in Safety (#257 of 329). Above par in 25 of 33 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 5 and Claude Fable 5 and ahead of Claude 3.7 Sonnet and MiniMax M3.

§ 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.

Human preference63.9#30/354
Human preference63.9#30/354
Agents55.6#51/298
Knowledge work59#53/208
Tool use60—/81✱
Workflow automation54.2—/0✱
Coding53.4#52/179
Agentic coding53.5#53/173
Code generation62—/20✱
Repository Q&A54.8—/0✱
Professional53.1#59/194
Finance55.3#44/162
Legal52.6#71/173
Medical51.3#77/149
Knowledge52.9#69/197
Academic knowledge56.9#38/123
Factuality54.5—/0✱
Reasoning51.8#82/195
Science56.6#47/122
Reasoning50#66/147
Mathematics50.8#81/152
Expert reasoning63.8—/0✱
Core abilities47.8#118/199
Language47.5#40/62
Instruction following39.9#51/62
General intelligence53.6#60/178
Long context60.2—/0✱
Safety46.5#257/329
Secure code59.5#69/270
Toxicity avoidance55.1#102/268
Fairness44.5#198/292
Harm refusal44.8#243/292
Jailbreak resistance30.6#251/268

§ 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 GLM-5.2, left for the other.

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

§ 3 · Sources

Where the numbers come from

11 publications, 55 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1475
GDPval-AA ↗1 measureread 2026-11-10
GDPval-AA 1381
AA-Briefcase ↗1 measureread 2026-11-10
AA-Briefcase 1226
ARC-AGI-2 ↗1 measureread 2026-11-10
ARC-AGI-2 22.8%
LiveBench 1.0 ↗8 measuresread 2026-11-10
LiveBench 1.0 73.2LiveBench 1.0 · Reasoning 78.6LiveBench 1.0 · Coding 79.7LiveBench 1.0 · Agentic Coding 51.8LiveBench 1.0 · Mathematics 89.8LiveBench 1.0 · Data Analysis 73.7LiveBench 1.0 · Language 76.2LiveBench 1.0 · Instruction Following 62.3
Kagi LLM Benchmark ↗1 measureread 2026-11-10
Kagi LLM Benchmark 60%
SimpleBench ↗1 measureread 2026-11-10
SimpleBench 58.8%
Vals.ai ↗12 measuresread 2026-11-10
Vals · Legal Research Bench 31.25%Vals · LegalBench 84.07%Vals · Finance Agent 49.7%Vals · CorpFin 66.12%Vals · TaxEval 73.34%Vals · MedCode 40.77%Vals · MedScribe 83.53%Vals · SWE-bench Verified 82.8% (Mini-SWE-agent)Vals · Vibe Code Bench 63.96% (OpenHands)Vals · Code Migration 37.87%Vals · GPQA Diamond 85.61%Vals · MMLU Pro 86.71%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10
Enkrypt · Jailbreak risk 29.1%Enkrypt · Harmful content risk 9.4%Enkrypt · CBRN risk 50.7%Enkrypt · Toxicity risk 2.7%Enkrypt · Bias risk 86.3%Enkrypt · Insecure code risk 13.8%
GDPVal-AA 1498tau3-Banking 34.6%Toolathlon Verified 59.9%Automation Bench Public 26.2%Apex-Agents (pass@1) 26.9%MCPMark 72.4%WildClawBench 55%Terminal-Bench 2.1 77.9%SciCode 50.5%SWE-Atlas-QnA 46.4%SWE Bench Pro 46.7%Humanity's Last Exam (without tools) 41.1%GPQA Diamond 89.5%CritPt 20.9%AA-LCR 76.7%AA-Omniscience Accuracy 24%AA-Omniscience Non-Hallucination 74%
GDPVal-AA (Elo) 1498Toolathlon Verified 59.9%Terminal-Bench 2.1 77.9%SWE-bench Pro (strict) 46.7%MCPMark 72.4%SWE-Atlas-QnA (strict) 46.4%

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✱ 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