Coding · Zhipu AI

GLM-4.5 Instruct on SWE-bench Verified: score, rank and what it means

GLM-4.5 Instruct scores 67.3 on SWE-bench Verified, placing it #161 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
67.3
0–100 scale
Rank
#161
of 600
Percentile
73th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
14.4
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with GLM-4.5 Instruct 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-4.5 Instruct sits at #161 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 14.4 points. The median model in this index scores 61.0, which puts GLM-4.5 Instruct above the midpoint.

Zhipu AI models average 57.7 on this benchmark. GLM-4.5 Instruct is 9.6 points above that provider line, so it is a stronger result than the average Zhipu AI model.

Among multimodal models, the average is 66.4. GLM-4.5 Instruct 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 67.3 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 $4.70 per million input tokens, GLM-4.5 Instruct is above 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
GLM-4.6 Zhipu AI 128000 $5.10 80.2
Nova Pro Max Amazon 1000000 $14.05 81.2
Reka Core Max Reka AI 128000 $13.41 79.3
Sonar Pro Perplexity 65536 $11.25 77.1
GLM-4.5 Instruct Zhipu AI 200000 $4.70 78.8
Kimi K1.5 Base Moonshot AI 65536 $4.34 77.4
QwQ Instruct Alibaba Cloud 65536 $4.62 79.0

Other benchmarks for GLM-4.5 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.1 119 80th
GPQA Diamond 75.3 139 77th
HumanEval 82.2 180 70th
MATH-500 79.6 217 64th
AIME 2025 74.3 168 72th
LiveCodeBench 74.8 97 84th
IFEval 84.4 202 66th
TruthfulQA 83.4 96 84th
HellaSwag 87.8 149 75th
MMMU 75.4 153 75th
Arena Elo 1410.6 183 70th

FAQ

What score does GLM-4.5 Instruct get on SWE-bench Verified?

GLM-4.5 Instruct scores 67.3 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does GLM-4.5 Instruct rank on SWE-bench Verified?

It ranks #161 of 600 models, in the 73rd percentile. The leader is GPT-5.2 Pro at 81.7.

Is GLM-4.5 Instruct good at SWE-bench Verified?

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 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-4.5 Instruct cost?

GLM-4.5 Instruct costs $4.70 per million input tokens and $22.79 per million output tokens.

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