Model Comparison

GLM-5 vs Magistral Small 2506Which is better in 2026?

Comparing GLM-5 and Magistral Small 2506 across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Magistral Small 2506 — which is better?

GLM-5 (by Zhipu AI) and Magistral Small 2506 (by Mistral AI) 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.

Choose GLM-5 if…

  • you want the most recent training data — it shipped Feb 2026

Choose Magistral Small 2506 if…

  • you are already invested in the Mistral AI ecosystem
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Magistral Small 2506don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

720.0B diff

GLM-5 has 720.0B more parameters than Magistral Small 2506, making it 3000.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
Mistral AI
Magistral Small 2506
24.0Bparameters
744.0B
GLM-5
24.0B
Magistral Small 2506

Context Window

Maximum input and output token capacity

Only GLM-5 specifies input context (200,000 tokens). Only GLM-5 specifies output context (128,000 tokens).

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Mistral AI
Magistral Small 2506
Input- tokens
Output- tokens
Thu Jun 11 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Magistral Small 2506 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

Magistral Small 2506

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Magistral Small 2506 was released on 2025-06-10.

GLM-5 is 8 months newer than Magistral Small 2506.

GLM-5

Feb 11, 2026

4 months ago

8mo newer
Magistral Small 2506

Jun 10, 2025

1.0 years ago

Knowledge Cutoff

When training data ends

Magistral Small 2506 has a documented knowledge cutoff of 2025-06-01, while GLM-5's cutoff date is not specified.

We can confirm Magistral Small 2506's training data extends to 2025-06-01, but cannot make a direct comparison without GLM-5's cutoff date.

GLM-5

—

Magistral Small 2506

Jun 2025

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
Mistral AI

No standout differentiators in the data we have for this pair.

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Mistral AI
Magistral Small 2506

FAQ

Common questions about GLM-5 vs Magistral Small 2506.

Which is better, GLM-5 or Magistral Small 2506?

GLM-5 (Zhipu AI) and Magistral Small 2506 (Mistral AI) 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 Magistral Small 2506 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%. Magistral Small 2506 scores AIME 2024: 70.7%, GPQA: 68.2%, AIME 2025: 62.8%, LiveCodeBench: 51.3%.

What are the context window sizes for GLM-5 and Magistral Small 2506?

GLM-5 supports 200K tokens and Magistral Small 2506 supports an unknown number of 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 Magistral Small 2506?

Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Magistral Small 2506?

GLM-5 is developed by Zhipu AI and Magistral Small 2506 is developed by Mistral AI.

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