Coding · Zhipu AI

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

GLM-4.5 Base scores 61.6 on SWE-bench Verified, placing it #289 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
61.6
0–100 scale
Rank
#289
of 600
Percentile
52th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
20.1
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with GLM-4.5 Base 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 Base sits at #289 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 20.1 points. The median model in this index scores 61.0, which puts GLM-4.5 Base above the midpoint.

Zhipu AI models average 57.7 on this benchmark. GLM-4.5 Base is 3.9 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 Base is 4.8 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 61.6 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 $3.99 per million input tokens, GLM-4.5 Base 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
Llama 3 Novita Novita AI 128000 $3.70 74.4
Nova Lite Pro Amazon 200000 $9.69 74.1
Reka Flash Pro Reka AI 200000 $10.82 75.2
Fusion Reasoning OpenRouter 65536 $8.59 72.2
GLM-4.5 Base Zhipu AI 32768 $3.99 74.9
Llama 3 Novita Chat Novita AI 65536 $3.50 74.2
Mistral Small 3 Chat Mistral AI 200000 $3.54 73.7

Other benchmarks for GLM-4.5 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.1 302 50th
GPQA Diamond 70.6 244 59th
HumanEval 78.7 270 55th
MATH-500 77.5 265 56th
AIME 2025 68.6 286 52th
LiveCodeBench 71.5 160 73th
IFEval 83.3 236 61th
TruthfulQA 76.5 291 52th
HellaSwag 84.6 261 57th
MMMU 74.4 172 71th
Arena Elo 1403.0 202 66th

FAQ

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

GLM-4.5 Base scores 61.6 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 Base rank on SWE-bench Verified?

It ranks #289 of 600 models, in the 52nd percentile. The leader is GPT-5.2 Pro at 81.7.

Is GLM-4.5 Base 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 Base cost?

GLM-4.5 Base costs $3.99 per million input tokens and $20.65 per million output tokens.

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