Reasoning · Zhipu AI

GLM-4.6 7B on GPQA Diamond: score, rank and what it means

GLM-4.6 7B scores 58.0 on GPQA Diamond, placing it #427 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
58.0
0–100 scale
Rank
#427
of 600
Percentile
29th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
29.0
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with GLM-4.6 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, GLM-4.6 7B sits at #427 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 29.0 points. The median model in this index scores 68.8, which puts GLM-4.6 7B below the midpoint.

Zhipu AI models average 65.7 on this benchmark. GLM-4.6 7B is 7.7 points below that provider line, so it is a weaker result than the average Zhipu AI model.

Among small open-weight models, the average is 49.3. GLM-4.6 7B is 8.7 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 58.0 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $1.52 per million input tokens, GLM-4.6 7B is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
SmolLM3 Instruct Hugging Face 8192 $1.69 63.6
Pythia Instruct EleutherAI 8192 $1.41 60.8
Hunyuan-Turbo Nano Tencent 32768 $4.65 62.7
DeepSeek-R1 8B DeepSeek 16384 $1.87 64.3
GLM-4.6 7B Zhipu AI 16384 $1.52 61.8
GPT-NeoX Chat EleutherAI 16384 $1.49 60.1
StableLM 2 Stability AI 8192 $1.91 65.0

Other benchmarks for GLM-4.6 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.6 443 26th
SWE-bench Verified 49.5 425 29th
HumanEval 66.6 424 29th
MATH-500 65.4 416 31th
AIME 2025 55.7 412 31th
LiveCodeBench 47.2 473 21th
IFEval 73.1 415 31th
TruthfulQA 65.6 451 25th
HellaSwag 75.4 434 28th
MMMU 58.2 456 24th
Arena Elo 1276.4 451 25th

FAQ

What score does GLM-4.6 7B get on GPQA Diamond?

GLM-4.6 7B scores 58.0 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does GLM-4.6 7B rank on GPQA Diamond?

It ranks #427 of 600 models, in the 29th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is GLM-4.6 7B good at GPQA Diamond?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the GPQA Diamond score calculated?

GPQA Diamond is a reasoning benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does GLM-4.6 7B cost?

GLM-4.6 7B costs $1.52 per million input tokens and $6.98 per million output tokens.

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