Model Comparison

GLM-5 vs Mistral Large 3 (675B Instruct 2512 NVFP4)Which is better in 2026?

Comparing GLM-5 and Mistral Large 3 (675B Instruct 2512 NVFP4) across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Mistral Large 3 (675B Instruct 2512 NVFP4) — which is better?

GLM-5 (by Zhipu AI) and Mistral Large 3 (675B Instruct 2512 NVFP4) (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 Mistral Large 3 (675B Instruct 2512 NVFP4) 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 Mistral Large 3 (675B Instruct 2512 NVFP4)don'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

69.0B diff

GLM-5 has 69.0B more parameters than Mistral Large 3 (675B Instruct 2512 NVFP4), making it 10.2% larger.

Zhipu AI
GLM-5
744.0Bparameters
Mistral AI
Mistral Large 3 (675B Instruct 2512 NVFP4)
675.0Bparameters
744.0B
GLM-5
675.0B
Mistral Large 3 (675B Instruct 2512 NVFP4)

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
Mistral Large 3 (675B Instruct 2512 NVFP4)
Input- tokens
Output- tokens
Wed Jun 10 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Large 3 (675B Instruct 2512 NVFP4) supports multimodal inputs, whereas GLM-5 does not.

Mistral Large 3 (675B Instruct 2512 NVFP4) can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

Mistral Large 3 (675B Instruct 2512 NVFP4)

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Mistral Large 3 (675B Instruct 2512 NVFP4) 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

Mistral Large 3 (675B Instruct 2512 NVFP4)

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Mistral Large 3 (675B Instruct 2512 NVFP4) was released on 2025-12-04.

GLM-5 is 2 months newer than Mistral Large 3 (675B Instruct 2512 NVFP4).

GLM-5

Feb 11, 2026

3 months ago

2mo newer
Mistral Large 3 (675B Instruct 2512 NVFP4)

Dec 4, 2025

6 months 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

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

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Mistral AI
Mistral Large 3 (675B Instruct 2512 NVFP4)

FAQ

Common questions about GLM-5 vs Mistral Large 3 (675B Instruct 2512 NVFP4).

Which is better, GLM-5 or Mistral Large 3 (675B Instruct 2512 NVFP4)?

GLM-5 (Zhipu AI) and Mistral Large 3 (675B Instruct 2512 NVFP4) (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 Mistral Large 3 (675B Instruct 2512 NVFP4) 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%. Mistral Large 3 (675B Instruct 2512 NVFP4) scores MMMLU: 85.5%, AMC_2022_23: 52.0%, GPQA: 43.9%, LiveCodeBench: 34.4%, SimpleQA: 23.8%.

What are the context window sizes for GLM-5 and Mistral Large 3 (675B Instruct 2512 NVFP4)?

GLM-5 supports 200K tokens and Mistral Large 3 (675B Instruct 2512 NVFP4) 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 Mistral Large 3 (675B Instruct 2512 NVFP4)?

Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Mistral Large 3 (675B Instruct 2512 NVFP4)?

GLM-5 is developed by Zhipu AI and Mistral Large 3 (675B Instruct 2512 NVFP4) is developed by Mistral AI.

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