Knowledge · Zhipu AI

GLM-4.5 Base on MMLU-Pro: score, rank and what it means

GLM-4.5 Base scores 76.1 on MMLU-Pro, placing it #302 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
76.1
0–100 scale
Rank
#302
of 600
Percentile
50th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
15.5
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with GLM-4.5 Base highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, GLM-4.5 Base sits at #302 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 15.5 points. The median model in this index scores 76.1, which puts GLM-4.5 Base above the midpoint.

Zhipu AI models average 73.5 on this benchmark. GLM-4.5 Base is 2.6 points above that provider line, so it is a stronger result than the average Zhipu AI model.

Among multimodal models, the average is 80.0. GLM-4.5 Base is 3.9 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 76.1 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 $3.99 per million input tokens, GLM-4.5 Base is below the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Reka Flash Pro Reka AI 200000 $10.82 75.2
Seed-OSS Chat ByteDance 65536 $3.49 74.4
Claude Opus 4.5 Nano Anthropic 32768 $9.38 73.3
Command R+ Base Cohere 65536 $3.24 71.6
GLM-4.5 Base Zhipu AI 32768 $3.99 74.9
Mixtral Chat Mistral AI 65536 $3.30 72.6
Phi-3.5 Microsoft 16384 $2.81 70.9

Other benchmarks for GLM-4.5 Base

BenchmarkScoreRankPercentileRelative
GPQA Diamond 70.6 244 59th
SWE-bench Verified 61.6 289 52th
HumanEval 78.7 270 55th
MATH-500 77.5 265 56th
AIME 2025 68.6 286 52th
LiveCodeBench 71.5 160 73th
IFEval 83.3 236 61th
TruthfulQA 76.5 291 52th
HellaSwag 84.6 261 57th
MMMU 74.4 172 71th
Arena Elo 1403.0 202 66th

FAQ

What score does GLM-4.5 Base get on MMLU-Pro?

GLM-4.5 Base scores 76.1 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does GLM-4.5 Base rank on MMLU-Pro?

It ranks #302 of 600 models, in the 50th percentile. The leader is GPT-5.2 Pro at 91.6.

Is GLM-4.5 Base good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 Base cost?

GLM-4.5 Base costs $3.99 per million input tokens and $20.65 per million output tokens.

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