Kimi K2-Thinking-0905 vs Muse Spark 1.3
Muse Spark 1.3 leads the LLM Stats Score 55.1 to 36.0. Muse Spark 1.3 is 6.8x cheaper per token.
Moonshot AI · Meta · Updated for 2026
Which is better?
Muse Spark 1.3 leads the overall LLM Stats Score 55.1 to 36.0, ranking #4 overall.
On price, Muse Spark 1.3 is roughly 6.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark 1.3 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-Thinking-0905
- you need open weights you can self-host or fine-tune
Choose Muse Spark 1.3
- overall performance matters — it scores 55.1 and ranks #4 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 6.8x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
21 reported for Kimi K2-Thinking-0905 · 11 for Muse Spark 1.3
Kimi K2-Thinking-0905 and Muse Spark 1.3don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2-Thinking-0905 ($0.47/1M tokens) is 4.7x more expensive than Muse Spark 1.3 ($0.10/1M tokens).
For output processing, Kimi K2-Thinking-0905 ($2.00/1M tokens) is 10.0x more expensive than Muse Spark 1.3 ($0.20/1M tokens).
In conclusion, Kimi K2-Thinking-0905 is more expensive than Muse Spark 1.3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark 1.3 accepts 1,048,576 input tokens compared to Kimi K2-Thinking-0905's 262,144 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while Kimi K2-Thinking-0905 is limited to 262,144 tokens.
Input capabilities
Documented input modalities across available providers
Muse Spark 1.3 supports multimodal inputs, whereas Kimi K2-Thinking-0905 does not.
Muse Spark 1.3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2-Thinking-0905
Muse Spark 1.3
License
Usage and distribution terms
Kimi K2-Thinking-0905 is licensed under MIT, while Muse Spark 1.3 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Kimi K2-Thinking-0905 was released on 2025-09-05, while Muse Spark 1.3 was released on 2026-09-02.
Muse Spark 1.3 is 12 months newer than Kimi K2-Thinking-0905.
Sep 5, 2025
1.0 years ago
Sep 2, 2026
6 days ago
12mo 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-Thinking-0905 is available from DeepInfra, Novita, Fireworks. Muse Spark 1.3 is available from Meta Model API.
Kimi K2-Thinking-0905
Muse Spark 1.3
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2-Thinking-0905 and Muse Spark 1.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2-Thinking-0905 vs Muse Spark 1.3.