Reasoning · Zhipu AI

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

GLM-4.6 1.5B scores 49.6 on GPQA Diamond, placing it #529 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
49.6
0–100 scale
Rank
#529
of 600
Percentile
12th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
37.4
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with GLM-4.6 1.5B 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-4.6 1.5B sits at #529 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 37.4 points. The median model in this index scores 68.8, which puts GLM-4.6 1.5B below the midpoint.

Zhipu AI models average 65.7 on this benchmark. GLM-4.6 1.5B is 16.1 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 49.3. GLM-4.6 1.5B is 0.3 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 49.6 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 GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
MiniMax-M2 1.5B MiniMax 16384 $0.84 54.6
Llama 3 Anyscale 7B Anyscale 4096 $0.98 56.2
Qwen3 1.5B Alibaba Cloud 4096 $0.84 53.5
Command R+ 7B Cohere 8192 $0.95 56.2
GLM-4.6 1.5B Zhipu AI 4096 $0.92 54.7
Llama 3 Baseten 7B Baseten 32768 $0.87 55.3
DBRX 8B Databricks 4096 $0.82 54.1

Other benchmarks for GLM-4.6 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 61.0 513 15th
SWE-bench Verified 39.8 524 13th
HumanEval 57.6 527 12th
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 GPQA Diamond?

GLM-4.6 1.5B scores 49.6 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does GLM-4.6 1.5B rank on GPQA Diamond?

It ranks #529 of 600 models, in the 12th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is GLM-4.6 1.5B good at GPQA Diamond?

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 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-4.6 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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