$ diff mistral-large-4 muse-spark-1-3
Mistral Large 4 vs Muse Spark 1.3
Values come from Mistral Large 4 and Muse Spark 1.3, where each is cited to its source. This page states no benchmark result and ranks neither model — it puts two published specifications next to each other. Where a lab has not published a figure, the row says so rather than guessing.
Mistral AIMistral Large 4
- context
- 1M
- weights
- —
- $/M in
- $1.36
- $/M out
- $4.18
- context
- 1M
- weights
- closed
- $/M in
- $1.25
- $/M out
- $4.25
What actually differs
- Context window
- Identical — both accept 1M tokens, so context length is not a reason to pick either.
- Input price
- Muse Spark 1.3 at $1.25/M against $1.36/M — 1.1× cheaper to feed. Standard rates: one of these labs also quotes a lower cached-input tier, which applies only when a prefix is reused — see the full spec below.
- Output price
- Mistral Large 4 at $4.18/M against $4.25/M — 1.0× cheaper to generate. Output dominates the bill on most agentic workloads, where the model writes far more than it reads.
- Recency
- Mistral Large 4 shipped 34 days after Muse Spark 1.3 (2026-10-06 vs 2026-09-02).
Full spec
| Attribute | Mistral Large 4 | Muse Spark 1.3 |
|---|---|---|
| Developer | Mistral AI | Meta AI |
| Released | 2026-10-06 | 2026-09-02 |
| Context window | 1M | 1,000,000 |
| Pricing | $1.36/M input · $4.18/M output (announcement) | Standard $1.25/M input · $4.25/M output · Contributor ≈$0.10/M input · ≈$0.20/M output |
| License | not recorded | proprietary |
| Availability | Mistral Studio API preview; weights promised by end of October 2026 | Muse Code, Meta Model API |