Model Comparison

GLM-5 vs Qwen2.5 72B InstructWhich is better in 2026?

Comparing GLM-5 and Qwen2.5 72B Instruct across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Qwen2.5 72B Instruct — which is better?

GLM-5 (by Zhipu AI) and Qwen2.5 72B 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 72B Instruct is roughly 4.3x 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 72B Instruct if…

  • cost matters — it's about 4.3x cheaper per token

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Qwen2.5 72B 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 72B Instruct costs less

For input processing, GLM-5 ($1.00/1M tokens) is 2.9x more expensive than Qwen2.5 72B Instruct ($0.35/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 8.0x more expensive than Qwen2.5 72B Instruct ($0.40/1M tokens).

In conclusion, GLM-5 is more expensive than Qwen2.5 72B Instruct.*

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

Lowest available price from all providers
Sat Jun 06 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerFriendliAI
Alibaba Cloud / Qwen Team
Qwen2.5 72B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

671.3B diff

GLM-5 has 671.3B more parameters than Qwen2.5 72B Instruct, making it 923.4% larger.

Zhipu AI
GLM-5
744.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 72B Instruct
72.7Bparameters
744.0B
GLM-5
72.7B
Qwen2.5 72B Instruct

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to Qwen2.5 72B Instruct's 131,072 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while Qwen2.5 72B Instruct is limited to 8,192 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 72B Instruct
Input131,072 tokens
Output8,192 tokens
Sat Jun 06 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Qwen2.5 72B Instruct uses Qwen.

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

GLM-5

MIT

Open weights

Qwen2.5 72B Instruct

Qwen

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Qwen2.5 72B Instruct was released on 2024-09-19.

GLM-5 is 17 months newer than Qwen2.5 72B Instruct.

GLM-5

Feb 11, 2026

3 months ago

1.4yr newer
Qwen2.5 72B 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 72B Instruct is available from DeepInfra, Hyperbolic, Fireworks, Together.

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 72B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
together logo
Together
Input Price:Input: $1.20/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Larger context window (200,000 tokens)
Alibaba Cloud / Qwen Team

Qwen2.5 72B Instruct

View details

Alibaba Cloud / Qwen Team

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 72B Instruct

FAQ

Common questions about GLM-5 vs Qwen2.5 72B Instruct.

Which is better, GLM-5 or Qwen2.5 72B Instruct?

GLM-5 (Zhipu AI) and Qwen2.5 72B 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 72B 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 72B Instruct scores GSM8k: 95.8%, MT-Bench: 93.5%, MBPP: 88.2%, MMLU-Redux: 86.8%, HumanEval: 86.6%.

Is GLM-5 cheaper than Qwen2.5 72B Instruct?

Qwen2.5 72B Instruct is 2.9x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. Qwen2.5 72B Instruct costs $0.35/M input and $0.40/M output via deepinfra.

What are the context window sizes for GLM-5 and Qwen2.5 72B Instruct?

GLM-5 supports 200K tokens and Qwen2.5 72B Instruct supports 131K 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 72B Instruct?

Key differences include context window (200K vs 131K), input pricing ($1.00 vs $0.35/M), licensing (MIT vs Qwen). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Qwen2.5 72B Instruct?

GLM-5 is developed by Zhipu AI and Qwen2.5 72B Instruct is developed by Alibaba Cloud / Qwen Team.