Mistral Large 4 vs Muse Spark Open
Mistral Large 4 and Muse Spark Open are closely matched at 45.6 and 44.9 on the LLM Stats Score. Mistral Large 4 is 1.9x cheaper per token.
Mistral AI · Meta · Updated for 2026
Which is better?
Mistral Large 4 and Muse Spark Open are closely matched on the overall LLM Stats Score at 45.6 and 44.9.
In the 3 individual benchmarks reported for both models, Mistral Large 4 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Mistral Large 4 is roughly 1.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark Open also accepts a larger context window (1,048,576 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 4
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- cost matters — it's about 1.9x cheaper per token
Choose Muse Spark Open
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
18 reported for Mistral Large 4 · 17 for Muse Spark Open
Mistral Large 4 outperforms in 3 benchmarks (DeepSWE 1.1, SciCode, SWE Atlas - Codebase QnA), while Muse Spark Open is better at 0 benchmarks.
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, Mistral Large 4 ($0.68/1M tokens) is 1.8x cheaper than Muse Spark Open ($1.25/1M tokens).
For output processing, Mistral Large 4 ($2.09/1M tokens) is 2.0x cheaper than Muse Spark Open ($4.25/1M tokens).
In conclusion, Muse Spark Open is more expensive than Mistral Large 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 4 has 234.0B more parameters than Muse Spark Open, making it 28.7% larger.
Context Window
Maximum input and output token capacity
Muse Spark Open accepts 1,048,576 input tokens compared to Mistral Large 4's 1,000,000 tokens. Only Muse Spark Open specifies output context (1,048,576 tokens).
Input capabilities
Documented input modalities across available providers
Both Mistral Large 4 and Muse Spark Open support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Mistral Large 4
Muse Spark Open
License
Usage and distribution terms
Mistral Large 4 is licensed under a proprietary license, while Muse Spark Open uses Muse Model License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Muse Model License
Open weights
Release Timeline
When each model was launched
Mistral Large 4 was released on 2026-10-06, while Muse Spark Open was released on 2026-10-15.
Muse Spark Open is 0 month newer than Mistral Large 4.
Oct 6, 2026
1 weeks ago
Oct 15, 2026
4 days ago
1w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Mistral Large 4 is available from Mistral AI. Muse Spark Open is available from Together.
Mistral Large 4
Muse Spark Open
Outputs Comparison
Judge for yourself.
Run your own prompts against Mistral Large 4 and Muse Spark Open side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Large 4 vs Muse Spark Open.