Model Comparison

GLM-4.5 vs Qwen2.5-Coder 32B Instruct

GLM-4.5 significantly outperforms across most benchmarks. Qwen2.5-Coder 32B Instruct is 7.8x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GLM-4.5 outperforms in 2 benchmarks (LiveCodeBench, MMLU-Pro), while Qwen2.5-Coder 32B Instruct is better at 0 benchmarks.

GLM-4.5 significantly outperforms across most benchmarks.

Mon May 25 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen2.5-Coder 32B Instruct costs less

For input processing, GLM-4.5 ($0.40/1M tokens) is 4.4x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).

For output processing, GLM-4.5 ($1.60/1M tokens) is 17.8x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).

In conclusion, GLM-4.5 is more expensive than Qwen2.5-Coder 32B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Mon May 25 2026 • llm-stats.com

GLM-4.5

Input tokens$0.40

Output tokens$1.60

Best providerDeepinfra

Qwen2.5-Coder 32B Instruct

Input tokens$0.09

Output tokens$0.09

Best providerLambda

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

323.0B diff

GLM-4.5 has 323.0B more parameters than Qwen2.5-Coder 32B Instruct, making it 1009.4% larger.

GLM-4.5

355.0Bparameters

Qwen2.5-Coder 32B Instruct

32.0Bparameters

355.0B

GLM-4.5

32.0B

Qwen2.5-Coder 32B Instruct

Context Window

Maximum input and output token capacity

GLM-4.5 accepts 131,072 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. GLM-4.5 can generate longer responses up to 131,072 tokens, while Qwen2.5-Coder 32B Instruct is limited to 128,000 tokens.

GLM-4.5

Input131,072 tokens

Output131,072 tokens

Qwen2.5-Coder 32B Instruct

Input128,000 tokens

Output128,000 tokens

Mon May 25 2026 • llm-stats.com

License

Usage and distribution terms

GLM-4.5 is licensed under MIT, while Qwen2.5-Coder 32B Instruct uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-4.5

MIT

Open weights

Qwen2.5-Coder 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.5 was released on 2025-07-28, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.

GLM-4.5 is 10 months newer than Qwen2.5-Coder 32B Instruct.

GLM-4.5

Jul 28, 2025

10 months ago

10mo newer

Qwen2.5-Coder 32B Instruct

Sep 19, 2024

1.7 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

GLM-4.5 is available from DeepInfra, Fireworks, Novita. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.

GLM-4.5

Deepinfra

Input Price:Input: $0.40/1MOutput Price:Output: $1.60/1M

Fireworks

Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M

Novita

Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M

Qwen2.5-Coder 32B Instruct

Lambda

Input Price:Input: $0.09/1MOutput Price:Output: $0.09/1M

Deepinfra

Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M

Hyperbolic

Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M

Fireworks

Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

GLM-4.5

View details

Zhipu AI

Larger context window (131,072 tokens)

Higher LiveCodeBench score (72.9% vs 31.4%)

Higher MMLU-Pro score (84.6% vs 50.4%)

Qwen2.5-Coder 32B Instruct

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens

Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature	GLM-4.5	Qwen2.5-Coder 32B Instruct

FAQ

Common questions about GLM-4.5 vs Qwen2.5-Coder 32B Instruct.

Which is better, GLM-4.5 or Qwen2.5-Coder 32B Instruct?

GLM-4.5 significantly outperforms across most benchmarks. GLM-4.5 is made by Zhipu AI and Qwen2.5-Coder 32B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GLM-4.5 compare to Qwen2.5-Coder 32B Instruct in benchmarks?

GLM-4.5 scores MATH-500: 98.2%, AIME 2024: 91.0%, MMLU-Pro: 84.6%, TAU-bench Retail: 79.7%, GPQA: 79.1%. Qwen2.5-Coder 32B Instruct scores HumanEval: 92.7%, GSM8k: 91.1%, MBPP: 90.2%, HellaSwag: 83.0%, Winogrande: 80.8%.

Is GLM-4.5 cheaper than Qwen2.5-Coder 32B Instruct?

Qwen2.5-Coder 32B Instruct is 4.4x cheaper for input tokens. GLM-4.5 costs $0.40/M input and $1.60/M output via deepinfra. Qwen2.5-Coder 32B Instruct costs $0.09/M input and $0.09/M output via lambda.

What are the context window sizes for GLM-4.5 and Qwen2.5-Coder 32B Instruct?

GLM-4.5 supports 131K tokens and Qwen2.5-Coder 32B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-4.5 and Qwen2.5-Coder 32B Instruct?

Key differences include context window (131K vs 128K), input pricing ($0.40 vs $0.09/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.5 and Qwen2.5-Coder 32B Instruct?

GLM-4.5 is developed by Zhipu AI and Qwen2.5-Coder 32B Instruct is developed by Alibaba Cloud / Qwen Team.