Mercury 3 vs Mistral Medium 3.5
Mercury 3 leads the LLM Stats Score 36.1 to 26.4. Mercury 3 is 18.5x cheaper per token.
Inception · Mistral AI · Updated for 2026
Which is better?
Mercury 3 leads the overall LLM Stats Score 36.1 to 26.4, ranking #98 overall.
In the 2 individual benchmarks reported for both models, Mercury 3 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Mercury 3 is roughly 18.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mercury 3 also accepts a larger context window (1,000,000 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 Mercury 3
- overall performance matters — it scores 36.1 and ranks #98 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 18.5x cheaper per token
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2026
Choose Mistral Medium 3.5
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
12 reported for Mercury 3 · 11 for Mistral Medium 3.5
Mercury 3 outperforms in 2 benchmarks (IFBench, Tau3 Banking), while Mistral Medium 3.5 is better at 0 benchmarks.
Mercury 3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Mercury 3 ($0.10/1M tokens) is 15.0x cheaper than Mistral Medium 3.5 ($1.50/1M tokens).
For output processing, Mercury 3 ($0.35/1M tokens) is 21.4x cheaper than Mistral Medium 3.5 ($7.50/1M tokens).
In conclusion, Mistral Medium 3.5 is more expensive than Mercury 3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Mercury 3 accepts 1,000,000 input tokens compared to Mistral Medium 3.5's 256,000 tokens. Mistral Medium 3.5 can generate longer responses up to 256,000 tokens, while Mercury 3 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Mistral Medium 3.5 supports multimodal inputs, whereas Mercury 3 does not.
Mistral Medium 3.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mercury 3
Mistral Medium 3.5
License
Usage and distribution terms
Mercury 3 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.
Proprietary
Closed source
Modified MIT License
Open weights
Release Timeline
When each model was launched
Mercury 3 was released on 2026-10-19, while Mistral Medium 3.5 was released on 2026-04-29.
Mercury 3 is 6 months newer than Mistral Medium 3.5.
Oct 19, 2026
6 days ago
5mo newerApr 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.
Provider Availability
Mercury 3 is available from Inception. Mistral Medium 3.5 is available from Mistral AI.
Mercury 3
Mistral Medium 3.5
Outputs Comparison
Judge for yourself.
Run your own prompts against Mercury 3 and Mistral Medium 3.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mercury 3 vs Mistral Medium 3.5.