Model Comparison

GLM-5 vs Qwen2.5-Coder 32B InstructWhich is better in 2026?

Comparing GLM-5 and Qwen2.5-Coder 32B Instruct across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Qwen2.5-Coder 32B Instruct — which is better?

GLM-5 (by Zhipu AI) and Qwen2.5-Coder 32B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

On price, Qwen2.5-Coder 32B Instruct is roughly 17.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GLM-5 also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose GLM-5 if…

  • you process long inputs — it offers a 200,000 token context window
  • you want the most recent training data — it shipped Feb 2026

Choose Qwen2.5-Coder 32B Instruct if…

  • cost matters — it's about 17.2x cheaper per token

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Qwen2.5-Coder 32B Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen2.5-Coder 32B Instruct costs less

For input processing, GLM-5 ($1.00/1M tokens) is 11.1x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 35.6x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).

In conclusion, GLM-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
Sun Jun 07 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerFriendliAI
Alibaba Cloud / Qwen Team
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

712.0B diff

GLM-5 has 712.0B more parameters than Qwen2.5-Coder 32B Instruct, making it 2225.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
32.0Bparameters
744.0B
GLM-5
32.0B
Qwen2.5-Coder 32B Instruct

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. Both models can generate responses up to 128,000 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
Input128,000 tokens
Output128,000 tokens
Sun Jun 07 2026 • llm-stats.com

License

Usage and distribution terms

GLM-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-5

MIT

Open weights

Qwen2.5-Coder 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.

GLM-5 is 17 months newer than Qwen2.5-Coder 32B Instruct.

GLM-5

Feb 11, 2026

3 months ago

1.4yr 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-5 is available from FriendliAI, ZAI. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.

GLM-5

friendli logo
FriendliAI
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M
z logo
Unknown Organization
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

Qwen2.5-Coder 32B Instruct

lambda logo
Lambda
Input Price:Input: $0.09/1MOutput Price:Output: $0.09/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
fireworks logo
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

Larger context window (200,000 tokens)
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct

FAQ

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

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

GLM-5 (Zhipu AI) and Qwen2.5-Coder 32B Instruct (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

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

GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. Qwen2.5-Coder 32B Instruct scores HumanEval: 92.7%, GSM8k: 91.1%, MBPP: 90.2%, HellaSwag: 83.0%, Winogrande: 80.8%.

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

Qwen2.5-Coder 32B Instruct is 11.1x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. 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-5 and Qwen2.5-Coder 32B Instruct?

GLM-5 supports 200K 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-5 and Qwen2.5-Coder 32B Instruct?

Key differences include context window (200K vs 128K), input pricing ($1.00 vs $0.09/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

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

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