Coding · Zhipu AI

GLM-4.5 Base on LiveCodeBench: score, rank and what it means

GLM-4.5 Base scores 71.5 on LiveCodeBench, placing it #160 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
71.5
0–100 scale
Rank
#160
of 600
Percentile
73th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
13.6
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with GLM-4.5 Base highlighted. Longer bars mean higher scores.

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, GLM-4.5 Base sits at #160 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 13.6 points. The median model in this index scores 64.7, which puts GLM-4.5 Base above the midpoint.

Zhipu AI models average 61.8 on this benchmark. GLM-4.5 Base is 9.7 points above that provider line, so it is a stronger result than the average Zhipu AI model.

Among multimodal models, the average is 70.3. GLM-4.5 Base is 1.2 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 71.5 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 LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Doubao 1.5 Pro Pro ByteDance 128000 $14.10 80.2
GLM-4.6 Zhipu AI 128000 $5.10 80.2
Grok 4 Mini xAI 65536 $12.21 77.9
Yi-Lightning 01.AI 32768 $4.22 77.2
GLM-4.5 Base Zhipu AI 32768 $3.99 74.9
Llama 3 Anyscale Instruct Anyscale 200000 $3.91 75.7
MiniMax-Text MiniMax 32768 $4.44 77.0

Other benchmarks for GLM-4.5 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.1 302 50th
GPQA Diamond 70.6 244 59th
SWE-bench Verified 61.6 289 52th
HumanEval 78.7 270 55th
MATH-500 77.5 265 56th
AIME 2025 68.6 286 52th
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 LiveCodeBench?

GLM-4.5 Base scores 71.5 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does GLM-4.5 Base rank on LiveCodeBench?

It ranks #160 of 600 models, in the 73rd percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is GLM-4.5 Base good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench 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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