Multimodal · Zhipu AI

GLM-4.6 8B on MMMU: score, rank and what it means

GLM-4.6 8B scores 62.8 on MMMU, placing it #401 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
62.8
0–100 scale
Rank
#401
of 600
Percentile
33th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
24.1
points

Score distribution

The chart shows the top 10 models on MMMU, with GLM-4.6 8B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, GLM-4.6 8B sits at #401 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 24.1 points. The median model in this index scores 70.0, which puts GLM-4.6 8B below the midpoint.

Zhipu AI models average 67.5 on this benchmark. GLM-4.6 8B is 4.7 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 52.4. GLM-4.6 8B is 10.4 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 62.8 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 $1.69 per million input tokens, GLM-4.6 8B is below the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Molmo Allen Institute for AI 32768 $2.49 68.5
Hunyuan-Turbo Nano Tencent 32768 $4.65 62.7
StableLM 2 Instruct Stability AI 16384 $1.93 65.2
Embed 4 Reasoning Cohere 4096 $5.50 65.3
GLM-4.6 8B Zhipu AI 8192 $1.69 63.1
DeepSeek-R1 8B DeepSeek 16384 $1.87 64.3
Llama 4 Maverick 8B Meta AI 4096 $1.64 63.4

Other benchmarks for GLM-4.6 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 69.1 406 32th
GPQA Diamond 59.3 410 32th
SWE-bench Verified 51.3 411 32th
HumanEval 64.7 444 26th
MATH-500 62.0 444 26th
AIME 2025 55.4 413 31th
LiveCodeBench 51.8 432 28th
IFEval 71.5 435 28th
TruthfulQA 67.9 412 31th
HellaSwag 78.7 395 34th
Arena Elo 1311.9 404 33th

FAQ

What score does GLM-4.6 8B get on MMMU?

GLM-4.6 8B scores 62.8 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does GLM-4.6 8B rank on MMMU?

It ranks #401 of 600 models, in the 33rd percentile. The leader is GPT-5.2 Max at 86.9.

Is GLM-4.6 8B good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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 8B cost?

GLM-4.6 8B costs $1.69 per million input tokens and $8.38 per million output tokens.

Related