Reasoning · Zhipu AI

GLM-4.5 Instruct on GPQA Diamond: score, rank and what it means

GLM-4.5 Instruct scores 75.3 on GPQA Diamond, placing it #139 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
75.3
0–100 scale
Rank
#139
of 600
Percentile
77th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
11.7
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with GLM-4.5 Instruct 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-4.5 Instruct sits at #139 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 11.7 points. The median model in this index scores 68.8, which puts GLM-4.5 Instruct above the midpoint.

Zhipu AI models average 65.7 on this benchmark. GLM-4.5 Instruct is 9.6 points above that provider line, so it is a stronger result than the average Zhipu AI model.

Among multimodal models, the average is 73.5. GLM-4.5 Instruct is 1.8 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 75.3 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 $4.70 per million input tokens, GLM-4.5 Instruct is above 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
Hunyuan-Large Chat Tencent 200000 $4.35 78.1
Hunyuan-Large Instruct Tencent 65536 $4.39 78.2
MiniMax-M2 MiniMax 200000 $5.19 80.6
Codestral Mistral AI 65536 $4.19 77.6
GLM-4.5 Instruct Zhipu AI 200000 $4.70 78.8
Claude Haiku 4.5 Turbo Anthropic 200000 $14.37 80.0
GLM-4.6 Base Zhipu AI 128000 $4.53 78.5

Other benchmarks for GLM-4.5 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.1 119 80th
SWE-bench Verified 67.3 161 73th
HumanEval 82.2 180 70th
MATH-500 79.6 217 64th
AIME 2025 74.3 168 72th
LiveCodeBench 74.8 97 84th
IFEval 84.4 202 66th
TruthfulQA 83.4 96 84th
HellaSwag 87.8 149 75th
MMMU 75.4 153 75th
Arena Elo 1410.6 183 70th

FAQ

What score does GLM-4.5 Instruct get on GPQA Diamond?

GLM-4.5 Instruct scores 75.3 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does GLM-4.5 Instruct rank on GPQA Diamond?

It ranks #139 of 600 models, in the 77th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is GLM-4.5 Instruct good at GPQA Diamond?

Yes, relative to the index: it is above the median and inside the top half of scores. 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-4.5 Instruct cost?

GLM-4.5 Instruct costs $4.70 per million input tokens and $22.79 per million output tokens.

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