Coding · Zhipu AI

GLM-4.6 8B on SWE-bench Verified: score, rank and what it means

GLM-4.6 8B scores 51.3 on SWE-bench Verified, placing it #411 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
51.3
0–100 scale
Rank
#411
of 600
Percentile
32th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
30.4
points

Score distribution

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

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, GLM-4.6 8B sits at #411 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 30.4 points. The median model in this index scores 61.0, which puts GLM-4.6 8B below the midpoint.

Zhipu AI models average 57.7 on this benchmark. GLM-4.6 8B is 6.4 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 39.0. GLM-4.6 8B is 12.3 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 51.3 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 SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
StableLM 2 Stability AI 8192 $1.91 65.0
Embed 4 Cohere 32768 $4.79 63.8
Phi-3.5 Base Microsoft 65536 $2.24 66.6
StableLM 2 Chat Stability AI 8192 $1.79 64.6
GLM-4.6 8B Zhipu AI 8192 $1.69 63.1
Zephyr Instruct Hugging Face 4096 $1.66 62.4
Qwen3 8B Alibaba Cloud 8192 $1.66 61.9

Other benchmarks for GLM-4.6 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 69.1 406 32th
GPQA Diamond 59.3 410 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
MMMU 62.8 401 33th
Arena Elo 1311.9 404 33th

FAQ

What score does GLM-4.6 8B get on SWE-bench Verified?

GLM-4.6 8B scores 51.3 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does GLM-4.6 8B rank on SWE-bench Verified?

It ranks #411 of 600 models, in the 32nd percentile. The leader is GPT-5.2 Pro at 81.7.

Is GLM-4.6 8B good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified 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 8B cost?

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

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