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Magistral Medium vs Parse

Comparing Magistral Medium and Parse across benchmarks, pricing, and capabilities.

Mistral AI · Cohere · Updated for 2026

Which is better?

Magistral Medium and Parse trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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

Choose Magistral Medium

  • you need open weights you can self-host or fine-tune

Choose Parse

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

At a glance

The differences that matter most.

Benchmark wins
Input price
— / M
— / M
Output price
— / M
— / M
Context window
8,192

Individual benchmarks

6 reported for Magistral Medium · 1 for Parse

No common benchmarks found

Magistral Medium and Parsedon'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

21.7B diff

Magistral Medium has 21.7B more parameters than Parse, making it 943.5% larger.

Mistral AI
Magistral Medium
24.0Bparameters
Cohere
Parse
2.3Bparameters
24.0B
Magistral Medium
2.3B
Parse

Context Window

Maximum input and output token capacity

Only Parse specifies input context (8,192 tokens).

Mistral AI
Magistral Medium
Input- tokens
Output- tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Magistral Medium and Parse support multimodal inputs.

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

Magistral Medium

Text
Images
Audio
Video

Parse

Text
Images
Audio
Video

License

Usage and distribution terms

Magistral Medium is licensed under Apache 2.0, while Parse uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

Magistral Medium

Apache 2.0

Open weights

Parse

Proprietary

Closed source

Release Timeline

When each model was launched

Magistral Medium was released on 2025-06-10, while Parse was released on 2026-08-27.

Parse is 15 months newer than Magistral Medium.

Magistral Medium

Jun 10, 2025

1.3 years ago

Parse

Aug 27, 2026

3 weeks ago

1.2yr newer

Knowledge Cutoff

When training data ends

Magistral Medium has a documented knowledge cutoff of 2025-06-01, while Parse'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 Parse's cutoff date.

Magistral Medium

Jun 2025

Parse

Outputs Comparison

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Judge for yourself.

Run your own prompts against Magistral Medium and Parse side-by-side, then vote on the output you prefer.

Magistral Medium
✓ Preferred
Parse
Open in Playground

FAQ

Common questions about Magistral Medium vs Parse.

Which is better, Magistral Medium or Parse?

Magistral Medium (Mistral AI) and Parse (Cohere) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Magistral Medium compare to Parse in benchmarks?

Magistral Medium scores AIME 2024: 73.6%, GPQA: 70.8%, AIME 2025: 64.9%, LiveCodeBench: 50.3%, Aider-Polyglot: 47.1%. Parse scores ParseBench: 79.2%.

What are the context window sizes for Magistral Medium and Parse?

Magistral Medium supports an unknown number of tokens and Parse supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Magistral Medium and Parse?

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

Who makes Magistral Medium and Parse?

Magistral Medium is developed by Mistral AI and Parse is developed by Cohere.