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MAI-Thinking-1 vs Mistral Medium 3.5

MAI-Thinking-1 and Mistral Medium 3.5 are closely matched at 33.0 and 26.9 on the LLM Stats Score.

Microsoft · Mistral AI · Updated for 2026

Which is better?

MAI-Thinking-1 and Mistral Medium 3.5 are closely matched on the overall LLM Stats Score at 33.0 and 26.9.

In the 3 individual benchmarks reported for both models, Mistral Medium 3.5 wins 2; this is a narrower head-to-head signal than the composite indexes.

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

Choose MAI-Thinking-1

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

Choose Mistral Medium 3.5

  • you value its reported benchmark strengths — it wins 2 of 3 exact shared results
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

MAI-Thinking-1
Microsoft
Mistral Medium 3.5
Mistral AI
Core performance indexes
LLM Stats Score
33.0
#110
26.9
#153
Reasoning
33.8
#101
27.2
#145
Coding
19.2
#115
23.7
#82
Agents
12.6
#106
8.9
#138
Cost, coverage & limits
Benchmark wins
1 of 3
2 of 3
Input price
— / M
$1.50 / M
Output price
— / M
$7.50 / M
Context window
—
256,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
MAI-Thinking-1
Mistral Medium 3.5
Math
33.7#54
18.9#174
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

23 reported for MAI-Thinking-1 · 11 for Mistral Medium 3.5

3 shared

MAI-Thinking-1 outperforms in 1 benchmarks (AIME 2025), while Mistral Medium 3.5 is better at 1 benchmark (SWE-Bench Verified).

Both models are evenly matched across the benchmarks.

Fri Oct 02 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

872.0B diff

MAI-Thinking-1 has 872.0B more parameters than Mistral Medium 3.5, making it 681.3% larger.

Microsoft
MAI-Thinking-1
1.0Tparameters
Mistral AI
Mistral Medium 3.5
128.0Bparameters
1000.0B
MAI-Thinking-1
128.0B
Mistral Medium 3.5

Context Window

Maximum input and output token capacity

Only Mistral Medium 3.5 specifies input context (256,000 tokens). Only Mistral Medium 3.5 specifies output context (256,000 tokens).

Microsoft
MAI-Thinking-1
Input- tokens
Output- tokens
Mistral AI
Mistral Medium 3.5
Input256,000 tokens
Output256,000 tokens
Fri Oct 02 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Mistral Medium 3.5 supports multimodal inputs, whereas MAI-Thinking-1 does not.

Mistral Medium 3.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.

MAI-Thinking-1

Text
Images
Audio
Video

Mistral Medium 3.5

Text
Images
Audio
Video

License

Usage and distribution terms

MAI-Thinking-1 is licensed under a proprietary license, while Mistral Medium 3.5 uses Modified MIT License.

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

MAI-Thinking-1

Proprietary

Closed source

Mistral Medium 3.5

Modified MIT License

Open weights

Release Timeline

When each model was launched

MAI-Thinking-1 was released on 2026-06-02, while Mistral Medium 3.5 was released on 2026-04-29.

MAI-Thinking-1 is 1 month newer than Mistral Medium 3.5.

MAI-Thinking-1

Jun 2, 2026

4 months ago

1mo newer
Mistral Medium 3.5

Apr 29, 2026

5 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?

Judge for yourself.

Run your own prompts against MAI-Thinking-1 and Mistral Medium 3.5 side-by-side, then vote on the output you prefer.

MAI-Thinking-1
✓ Preferred
Mistral Medium 3.5
Open in Playground

FAQ

Common questions about MAI-Thinking-1 vs Mistral Medium 3.5.

Which is better, MAI-Thinking-1 or Mistral Medium 3.5?

MAI-Thinking-1 and Mistral Medium 3.5 are closely matched on the LLM Stats Score at 33.0 and 26.9. MAI-Thinking-1 is made by Microsoft and Mistral Medium 3.5 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 MAI-Thinking-1 compare to Mistral Medium 3.5 in benchmarks?

MAI-Thinking-1 scores LongFact: 98.0%, AIME 2025: 97.0%, AIME 2026: 94.5%, GraphWalks: 90.0%, AIR-Bench: 88.0%. Mistral Medium 3.5 scores COLLIE: 95.8%, Tau3 Telecom: 91.4%, AIME 2025: 86.3%, SWE-Bench Verified: 77.6%, Tau3 Retail: 76.1%.

What are the context window sizes for MAI-Thinking-1 and Mistral Medium 3.5?

MAI-Thinking-1 supports an unknown number of tokens and Mistral Medium 3.5 supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between MAI-Thinking-1 and Mistral Medium 3.5?

Key differences include LLM Stats Score (33.0 vs 26.9), multimodal support (no vs yes), licensing (Proprietary vs Modified MIT License). See the full comparison above for benchmark-by-benchmark results.

Who makes MAI-Thinking-1 and Mistral Medium 3.5?

MAI-Thinking-1 is developed by Microsoft and Mistral Medium 3.5 is developed by Mistral AI.

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