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GLM-5.3-Flash vs Mistral Large 3 (675B Instruct 2512 NVFP4)

Comparing GLM-5.3-Flash and Mistral Large 3 (675B Instruct 2512 NVFP4) across benchmarks, pricing, and capabilities.

Zhipu AI · Mistral AI · Updated for 2026

Which is better?

GLM-5.3-Flash and Mistral Large 3 (675B Instruct 2512 NVFP4) trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Based on current benchmark, pricing, and model metadata for 2026.

Choose GLM-5.3-Flash

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

Choose Mistral Large 3 (675B Instruct 2512 NVFP4)

  • you are already invested in the Mistral AI ecosystem

At a glance

The differences that matter most.

GLM-5.3-Flash
Zhipu AI
Mistral Large 3 (675B Instruct 2512 NVFP4)
Mistral AI
Benchmark wins
—
—
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,000,000
—
Released
Aug 2026
Dec 2025
License
MIT
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3-Flash 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

Playground indexes and blind preference scores

Model Size

Parameter count comparison

355.0B diff

Mistral Large 3 (675B Instruct 2512 NVFP4) has 355.0B more parameters than GLM-5.3-Flash, making it 110.9% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
Mistral AI
Mistral Large 3 (675B Instruct 2512 NVFP4)
675.0Bparameters
320.0B
GLM-5.3-Flash
675.0B
Mistral Large 3 (675B Instruct 2512 NVFP4)

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,000,000 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,000,000 tokens
Output131,072 tokens
Mistral AI
Mistral Large 3 (675B Instruct 2512 NVFP4)
Input- tokens
Output- tokens
Wed Aug 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both GLM-5.3-Flash and Mistral Large 3 (675B Instruct 2512 NVFP4) support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GLM-5.3-Flash

Text
Images
Audio
Video

Mistral Large 3 (675B Instruct 2512 NVFP4)

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash 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-5.3-Flash

MIT

Open weights

Mistral Large 3 (675B Instruct 2512 NVFP4)

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while Mistral Large 3 (675B Instruct 2512 NVFP4) was released on 2025-12-04.

GLM-5.3-Flash is 9 months newer than Mistral Large 3 (675B Instruct 2512 NVFP4).

GLM-5.3-Flash

Aug 26, 2026

0 days ago

8mo newer
Mistral Large 3 (675B Instruct 2512 NVFP4)

Dec 4, 2025

8 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→

Judge for yourself.

Run your own prompts against GLM-5.3-Flash and Mistral Large 3 (675B Instruct 2512 NVFP4) side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
Mistral Large 3 (675B Instruct 2512 NVFP4)
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs Mistral Large 3 (675B Instruct 2512 NVFP4).

Which is better, GLM-5.3-Flash or Mistral Large 3 (675B Instruct 2512 NVFP4)?

GLM-5.3-Flash (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-5.3-Flash compare to Mistral Large 3 (675B Instruct 2512 NVFP4) in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, MVBench: 77.8%. 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-5.3-Flash and Mistral Large 3 (675B Instruct 2512 NVFP4)?

GLM-5.3-Flash supports 1.0M 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-5.3-Flash and Mistral Large 3 (675B Instruct 2512 NVFP4)?

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

Who makes GLM-5.3-Flash and Mistral Large 3 (675B Instruct 2512 NVFP4)?

GLM-5.3-Flash is developed by Zhipu AI and Mistral Large 3 (675B Instruct 2512 NVFP4) is developed by Mistral AI.

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