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Mistral Large 2 vs Parse

Comparing Mistral Large 2 and Parse across benchmarks, pricing, and capabilities.

Mistral AI · Cohere · Updated for 2026

Which is better?

Mistral Large 2 and Parse trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

Mistral Large 2 also accepts a larger context window (128,000 input tokens), making it the stronger choice for long documents and large codebases.

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

Choose Mistral Large 2

  • you process long inputs — it offers a 128,000 token context window
  • 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
$2.00 / M
— / M
Output price
$6.00 / M
— / M
Context window
128,000
8,192

Individual benchmarks

5 reported for Mistral Large 2 · 1 for Parse

No common benchmarks found

Mistral Large 2 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

120.7B diff

Mistral Large 2 has 120.7B more parameters than Parse, making it 5247.8% larger.

Mistral AI
Mistral Large 2
123.0Bparameters
Cohere
Parse
2.3Bparameters
123.0B
Mistral Large 2
2.3B
Parse

Context Window

Maximum input and output token capacity

Mistral Large 2 accepts 128,000 input tokens compared to Parse's 8,192 tokens. Only Mistral Large 2 specifies output context (128,000 tokens).

Mistral AI
Mistral Large 2
Input128,000 tokens
Output128,000 tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Thu Sep 03 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Parse supports multimodal inputs, whereas Mistral Large 2 does not.

Parse can handle both text and other forms of data like images, making it suitable for multimodal applications.

Mistral Large 2

Text
Images
Audio
Video

Parse

Text
Images
Audio
Video

License

Usage and distribution terms

Mistral Large 2 is licensed under Mistral Research License, while Parse uses a proprietary license.

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

Mistral Large 2

Mistral Research License

Open weights

Parse

Proprietary

Closed source

Release Timeline

When each model was launched

Mistral Large 2 was released on 2024-07-24, while Parse was released on 2026-08-27.

Parse is 25 months newer than Mistral Large 2.

Mistral Large 2

Jul 24, 2024

2.1 years ago

Parse

Aug 27, 2026

6 days ago

2.1yr newer

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

Provider Availability

Mistral Large 2 is available from Google, Mistral AI. Parse is available from Azure, Cohere.

Mistral Large 2

google logo
Google
Input Price:Input: $2.00/1MOutput Price:Output: $6.00/1M
mistral logo
Mistral
Input Price:Input: $2.00/1MOutput Price:Output: $6.00/1M

Parse

azure logo
Azure
cohere logo
Cohere
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Mistral Large 2 and Parse side-by-side, then vote on the output you prefer.

Mistral Large 2
✓ Preferred
Parse
Open in Playground

FAQ

Common questions about Mistral Large 2 vs Parse.

Which is better, Mistral Large 2 or Parse?

Mistral Large 2 (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 Mistral Large 2 compare to Parse in benchmarks?

Mistral Large 2 scores GSM8k: 93.0%, HumanEval: 92.0%, MT-Bench: 86.3%, MMLU: 84.0%, MMLU French: 82.8%. Parse scores ParseBench: 79.2%.

What are the context window sizes for Mistral Large 2 and Parse?

Mistral Large 2 supports 128K 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 Mistral Large 2 and Parse?

Key differences include context window (128K vs 8K), multimodal support (no vs yes), licensing (Mistral Research License vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Mistral Large 2 and Parse?

Mistral Large 2 is developed by Mistral AI and Parse is developed by Cohere.