Instruction following · Zhipu AI

GLM-4.5 Instruct on IFEval: score, rank and what it means

GLM-4.5 Instruct scores 84.4 on IFEval, placing it #202 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.

Score
84.4
0–100 scale
Rank
#202
of 600
Percentile
66th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
11.7
points

Score distribution

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

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
8 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 o4 Reasoning OpenAI 1000000 $19.69 87.5

What this score means

On IFEval, GLM-4.5 Instruct sits at #202 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 11.7 points. The median model in this index scores 81.2, which puts GLM-4.5 Instruct above the midpoint.

Zhipu AI models average 79.1 on this benchmark. GLM-4.5 Instruct is 5.3 points above that provider line, so it is a stronger result than the average Zhipu AI model.

Among multimodal models, the average is 85.2. GLM-4.5 Instruct is 0.8 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 84.4 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 IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Sonar Perplexity 200000 $10.57 76.0
Llama 3.1 Cerebras Cerebras 128000 $4.01 76.0
o4 Mini OpenAI 200000 $11.92 77.7
GLM-4.5 Chat Zhipu AI 65536 $4.53 78.3
GLM-4.5 Instruct Zhipu AI 200000 $4.70 78.8
Grok 4 Mini xAI 65536 $12.21 77.9
Hunyuan-Large Tencent 65536 $4.33 78.2

Other benchmarks for GLM-4.5 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.1 119 80th
GPQA Diamond 75.3 139 77th
SWE-bench Verified 67.3 161 73th
HumanEval 82.2 180 70th
MATH-500 79.6 217 64th
AIME 2025 74.3 168 72th
LiveCodeBench 74.8 97 84th
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 IFEval?

GLM-4.5 Instruct scores 84.4 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does GLM-4.5 Instruct rank on IFEval?

It ranks #202 of 600 models, in the 66th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is GLM-4.5 Instruct good at IFEval?

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 IFEval score calculated?

IFEval is a instruction following 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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