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

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 8.8.

Zhipu AI · Mistral AI · Updated for 2026

Which is better?

GLM-5.3-Flash leads the overall LLM Stats Score 51.6 to 8.8, ranking #11 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GLM-5.3-Flash

  • overall performance matters — it scores 51.6 and ranks #11 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Aug 2026

Choose Mistral Large 3 (675B Instruct 2512 Eagle)

  • 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 Eagle)
Mistral AI
Core performance indexes
LLM Stats Score
51.6
#11
8.8
#258
Reasoning
50.3
#13
9.0
#249
Coding
37.8
#22
1.2
#216
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.15 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,048,576
—

Individual benchmarks

15 reported for GLM-5.3-Flash · 5 for Mistral Large 3 (675B Instruct 2512 Eagle)

No common benchmarks found

GLM-5.3-Flash and Mistral Large 3 (675B Instruct 2512 Eagle)don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

355.0B diff

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

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 Large 3 (675B Instruct 2512 Eagle)
Input- tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GLM-5.3-Flash and Mistral Large 3 (675B Instruct 2512 Eagle) 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 Eagle)

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5.3-Flash is licensed under MIT, while Mistral Large 3 (675B Instruct 2512 Eagle) 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 Eagle)

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 Eagle) was released on 2025-12-04.

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

GLM-5.3-Flash

Aug 26, 2026

2 days ago

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

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 Eagle) side-by-side, then vote on the output you prefer.

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

FAQ

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

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

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 8.8. GLM-5.3-Flash is made by Zhipu AI and Mistral Large 3 (675B Instruct 2512 Eagle) is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-5.3-Flash compare to Mistral Large 3 (675B Instruct 2512 Eagle) 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 Large 3 (675B Instruct 2512 Eagle) 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 Eagle)?

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

Key differences include LLM Stats Score (51.6 vs 8.8), 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 Eagle)?

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

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