Coding · Zhipu AI

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

GLM-4.5 Base scores 78.7 on HumanEval, placing it #270 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
78.7
0–100 scale
Rank
#270
of 600
Percentile
55th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
18.1
points

Score distribution

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

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, GLM-4.5 Base sits at #270 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 18.1 points. The median model in this index scores 77.4, which puts GLM-4.5 Base above the midpoint.

Zhipu AI models average 74.4 on this benchmark. GLM-4.5 Base is 4.3 points above that provider line, so it is a stronger result than the average Zhipu AI model.

Among multimodal models, the average is 82.2. GLM-4.5 Base is 3.5 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 78.7 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 HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Sonar Pro Perplexity 65536 $11.25 77.1
GPT-4.1 Mini OpenAI 128000 $10.43 74.3
Llama 3 Modal Base Modal 16384 $3.21 72.2
Llama 3 Modal Modal 32768 $3.82 74.9
GLM-4.5 Base Zhipu AI 32768 $3.99 74.9
Mixtral Groq Groq 16384 $3.37 73.1
Sonar Turbo Perplexity 65536 $10.71 75.7

Other benchmarks for GLM-4.5 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.1 302 50th
GPQA Diamond 70.6 244 59th
SWE-bench Verified 61.6 289 52th
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 HumanEval?

GLM-4.5 Base scores 78.7 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does GLM-4.5 Base rank on HumanEval?

It ranks #270 of 600 models, in the 55th percentile. The leader is GPT-5.2 Pro at 96.8.

Is GLM-4.5 Base good at HumanEval?

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 HumanEval score calculated?

HumanEval is a coding 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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