Coding · Zhipu AI

GLM-4.6 1.5B on HumanEval: score, rank and what it means

GLM-4.6 1.5B scores 57.6 on HumanEval, placing it #527 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
57.6
0–100 scale
Rank
#527
of 600
Percentile
12th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
39.2
points

Score distribution

The chart shows the top 10 models on HumanEval, with GLM-4.6 1.5B 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-4.6 1.5B sits at #527 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 39.2 points. The median model in this index scores 77.4, which puts GLM-4.6 1.5B below the midpoint.

Zhipu AI models average 74.4 on this benchmark. GLM-4.6 1.5B is 16.8 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 56.7. GLM-4.6 1.5B is 0.9 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 57.6 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 $0.92 per million input tokens, GLM-4.6 1.5B 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
Llama 3 Modal 8B Modal 32768 $0.98 56.6
Magistral 1.5B Mistral AI 4096 $0.67 52.7
Yi-Lightning 7B 01.AI 32768 $1.00 55.9
Llama 3 Baseten 7B Baseten 32768 $0.87 55.3
GLM-4.6 1.5B Zhipu AI 4096 $0.92 54.7
Mixtral Turbo 8B Together AI 4096 $0.75 54.1
Llama 3.3 1.5B Meta AI 4096 $0.61 52.2

Other benchmarks for GLM-4.6 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 61.0 513 15th
GPQA Diamond 49.6 529 12th
SWE-bench Verified 39.8 524 13th
MATH-500 56.3 503 16th
AIME 2025 42.9 523 13th
LiveCodeBench 43.8 508 15th
IFEval 67.7 492 18th
TruthfulQA 59.6 534 11th
HellaSwag 69.6 540 10th
MMMU 53.5 513 15th
Arena Elo 1225.9 530 12th

FAQ

What score does GLM-4.6 1.5B get on HumanEval?

GLM-4.6 1.5B scores 57.6 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does GLM-4.6 1.5B rank on HumanEval?

It ranks #527 of 600 models, in the 12th percentile. The leader is GPT-5.2 Pro at 96.8.

Is GLM-4.6 1.5B good at HumanEval?

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 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-4.6 1.5B cost?

GLM-4.6 1.5B costs $0.92 per million input tokens and $4.40 per million output tokens.

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