Mercury 2 vs Mistral Large 4
Mistral Large 4 leads the LLM Stats Score 46.2 to 23.5. Mercury 2 is 2.8x cheaper per token.
Inception · Mistral AI · Updated for 2026
Which is better?
Mistral Large 4 leads the overall LLM Stats Score 46.2 to 23.5, ranking #34 overall.
In the 1 individual benchmarks reported for both models, Mistral Large 4 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Mercury 2 is roughly 2.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mistral Large 4 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 2
- cost matters — it's about 2.8x cheaper per token
Choose Mistral Large 4
- overall performance matters — it scores 46.2 and ranks #34 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
6 reported for Mercury 2 · 18 for Mistral Large 4
Mercury 2 outperforms in 0 benchmarks, while Mistral Large 4 is better at 1 benchmark (SciCode).
Mistral Large 4 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 2 ($0.25/1M tokens) is 2.7x cheaper than Mistral Large 4 ($0.68/1M tokens).
For output processing, Mercury 2 ($0.75/1M tokens) is 2.8x cheaper than Mistral Large 4 ($2.09/1M tokens).
In conclusion, Mistral Large 4 is more expensive than Mercury 2.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Mistral Large 4 accepts 1,000,000 input tokens compared to Mercury 2's 128,000 tokens. Only Mercury 2 specifies output context (8,192 tokens).
Input capabilities
Documented input modalities across available providers
Mistral Large 4 supports multimodal inputs, whereas Mercury 2 does not.
Mistral Large 4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mercury 2
Mistral Large 4
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Mercury 2 was released on 2026-02-24, while Mistral Large 4 was released on 2026-10-06.
Mistral Large 4 is 7 months newer than Mercury 2.
Feb 24, 2026
7 months ago
Oct 6, 2026
5 days ago
7mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Mercury 2 is available from Inception. Mistral Large 4 is available from Mistral AI.
Mercury 2
Mistral Large 4
Outputs Comparison
Judge for yourself.
Run your own prompts against Mercury 2 and Mistral Large 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mercury 2 vs Mistral Large 4.