Model Comparison

GLM-4.5 vs Magistral Medium

GLM-4.5 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

GLM-4.5 outperforms in 4 benchmarks (AIME 2024, GPQA, Humanity's Last Exam, LiveCodeBench), while Magistral Medium is better at 0 benchmarks.

GLM-4.5 significantly outperforms across most benchmarks.

Sun Apr 19 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sun Apr 19 2026 • llm-stats.com
Zhipu AI
GLM-4.5
Input tokens$0.40
Output tokens$1.60
Best providerDeepinfra
Mistral AI
Magistral Medium
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

331.0B diff

GLM-4.5 has 331.0B more parameters than Magistral Medium, making it 1379.2% larger.

Zhipu AI
GLM-4.5
355.0Bparameters
Mistral AI
Magistral Medium
24.0Bparameters
355.0B
GLM-4.5
24.0B
Magistral Medium

Context Window

Maximum input and output token capacity

Only GLM-4.5 specifies input context (131,072 tokens). Only GLM-4.5 specifies output context (131,072 tokens).

Zhipu AI
GLM-4.5
Input131,072 tokens
Output131,072 tokens
Mistral AI
Magistral Medium
Input- tokens
Output- tokens
Sun Apr 19 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Magistral Medium supports multimodal inputs, whereas GLM-4.5 does not.

Magistral Medium can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.5

Text
Images
Audio
Video

Magistral Medium

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.5 is licensed under MIT, while Magistral Medium 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

Magistral Medium

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.5 was released on 2025-07-28, while Magistral Medium was released on 2025-06-10.

GLM-4.5 is 2 months newer than Magistral Medium.

GLM-4.5

Jul 28, 2025

8 months ago

1mo newer
Magistral Medium

Jun 10, 2025

10 months ago

Knowledge Cutoff

When training data ends

Magistral Medium has a documented knowledge cutoff of 2025-06-01, while GLM-4.5's cutoff date is not specified.

We can confirm Magistral Medium's training data extends to 2025-06-01, but cannot make a direct comparison without GLM-4.5's cutoff date.

GLM-4.5

—

Magistral Medium

Jun 2025

Outputs Comparison

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Key Takeaways

Zhipu AI
Larger context window (131,072 tokens)
Higher AIME 2024 score (91.0% vs 73.6%)
Higher GPQA score (79.1% vs 70.8%)
Higher Humanity's Last Exam score (14.4% vs 9.0%)
Higher LiveCodeBench score (72.9% vs 50.3%)
Mistral AI
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-4.5
Mistral AI
Magistral Medium

FAQ

Common questions about GLM-4.5 vs Magistral Medium

GLM-4.5 significantly outperforms across most benchmarks. GLM-4.5 is made by Zhipu AI and Magistral Medium is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GLM-4.5 scores MATH-500: 98.2%, AIME 2024: 91.0%, MMLU-Pro: 84.6%, TAU-bench Retail: 79.7%, GPQA: 79.1%. Magistral Medium scores AIME 2024: 73.6%, GPQA: 70.8%, AIME 2025: 64.9%, LiveCodeBench: 50.3%, Aider-Polyglot: 47.1%.
GLM-4.5 supports 131K tokens and Magistral Medium supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
GLM-4.5 is developed by Zhipu AI and Magistral Medium is developed by Mistral AI.