Kimi K2 Instruct vs Muse Spark Open
Muse Spark Open leads the LLM Stats Score 44.9 to 21.6. Kimi K2 Instruct is 4.0x cheaper per token.
Moonshot AI · Meta · Updated for 2026
Which is better?
Muse Spark Open leads the overall LLM Stats Score 44.9 to 21.6, ranking #43 overall.
In the 1 individual benchmarks reported for both models, Muse Spark Open wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Kimi K2 Instruct is roughly 4.0x 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 Kimi K2 Instruct
- cost matters — it's about 4.0x cheaper per token
Choose Muse Spark Open
- overall performance matters — it scores 44.9 and ranks #43 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 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
38 reported for Kimi K2 Instruct · 17 for Muse Spark Open
Kimi K2 Instruct outperforms in 0 benchmarks, while Muse Spark Open is better at 1 benchmark (GPQA).
Muse Spark Open 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, Kimi K2 Instruct ($0.50/1M tokens) is 2.5x cheaper than Muse Spark Open ($1.25/1M tokens).
For output processing, Kimi K2 Instruct ($0.50/1M tokens) is 8.5x cheaper than Muse Spark Open ($4.25/1M tokens).
In conclusion, Muse Spark Open is more expensive than Kimi K2 Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2 Instruct has 184.0B more parameters than Muse Spark Open, making it 22.5% larger.
Context Window
Maximum input and output token capacity
Muse Spark Open accepts 1,048,576 input tokens compared to Kimi K2 Instruct's 200,000 tokens. Muse Spark Open can generate longer responses up to 1,048,576 tokens, while Kimi K2 Instruct is limited to 200,000 tokens.
Input capabilities
Documented input modalities across available providers
Muse Spark Open supports multimodal inputs, whereas Kimi K2 Instruct does not.
Muse Spark Open can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2 Instruct
Muse Spark Open
License
Usage and distribution terms
Kimi K2 Instruct is licensed under MIT, while Muse Spark Open uses Muse Model License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Muse Model License
Open weights
Release Timeline
When each model was launched
Kimi K2 Instruct was released on 2025-07-11, while Muse Spark Open was released on 2026-10-15.
Muse Spark Open is 15 months newer than Kimi K2 Instruct.
Jul 11, 2025
1.3 years ago
Oct 15, 2026
4 days ago
1.3yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Kimi K2 Instruct is available from Fireworks, Novita. Muse Spark Open is available from Together.
Kimi K2 Instruct
Muse Spark Open
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2 Instruct and Muse Spark Open side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2 Instruct vs Muse Spark Open.