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GLM-5.3-Flash vs Mistral Small 3.2 24B Instruct

Comparing GLM-5.3-Flash and Mistral Small 3.2 24B Instruct across benchmarks, pricing, and capabilities.

Zhipu AI · Mistral AI · Updated for 2026

Which is better?

GLM-5.3-Flash and Mistral Small 3.2 24B Instruct 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 Small 3.2 24B Instruct

  • you are already invested in the Mistral AI ecosystem

At a glance

The differences that matter most.

GLM-5.3-Flash
Zhipu AI
Mistral Small 3.2 24B Instruct
Mistral AI
Benchmark wins
—
—
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
—
Released
Aug 2026
Jun 2025
License
MIT
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3-Flash and Mistral Small 3.2 24B Instructdon'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

296.4B diff

GLM-5.3-Flash has 296.4B more parameters than Mistral Small 3.2 24B Instruct, making it 1255.9% larger.

Zhipu AI
GLM-5.3-Flash
320.0Bparameters
Mistral AI
Mistral Small 3.2 24B Instruct
23.6Bparameters
320.0B
GLM-5.3-Flash
23.6B
Mistral Small 3.2 24B Instruct

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
Mistral AI
Mistral Small 3.2 24B Instruct
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 Small 3.2 24B Instruct 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 Small 3.2 24B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash is licensed under MIT, while Mistral Small 3.2 24B Instruct 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 Small 3.2 24B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5.3-Flash was released on 2026-08-26, while Mistral Small 3.2 24B Instruct was released on 2025-06-20.

GLM-5.3-Flash is 14 months newer than Mistral Small 3.2 24B Instruct.

GLM-5.3-Flash

Aug 26, 2026

0 days ago

1.2yr newer
Mistral Small 3.2 24B Instruct

Jun 20, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

Mistral Small 3.2 24B Instruct has a documented knowledge cutoff of 2023-10-01, while GLM-5.3-Flash's cutoff date is not specified.

We can confirm Mistral Small 3.2 24B Instruct's training data extends to 2023-10-01, but cannot make a direct comparison without GLM-5.3-Flash's cutoff date.

GLM-5.3-Flash

—

Mistral Small 3.2 24B Instruct

Oct 2023

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 Small 3.2 24B Instruct side-by-side, then vote on the output you prefer.

GLM-5.3-Flash
✓ Preferred
Mistral Small 3.2 24B Instruct
Open in Playground

FAQ

Common questions about GLM-5.3-Flash vs Mistral Small 3.2 24B Instruct.

Which is better, GLM-5.3-Flash or Mistral Small 3.2 24B Instruct?

GLM-5.3-Flash (Zhipu AI) and Mistral Small 3.2 24B Instruct (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 Small 3.2 24B Instruct in benchmarks?

GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%. Mistral Small 3.2 24B Instruct scores DocVQA: 94.9%, AI2D: 92.9%, HumanEval Plus: 92.9%, ChartQA: 87.4%, IF: 84.8%.

What are the context window sizes for GLM-5.3-Flash and Mistral Small 3.2 24B Instruct?

GLM-5.3-Flash supports 1.0M tokens and Mistral Small 3.2 24B Instruct 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 Small 3.2 24B Instruct?

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 Small 3.2 24B Instruct?

GLM-5.3-Flash is developed by Zhipu AI and Mistral Small 3.2 24B Instruct is developed by Mistral AI.

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