The AI arena is free today

Open Superagent

Kimi K2-Instruct-0905 vs Muse Spark 1.3

Muse Spark 1.3 leads the LLM Stats Score 55.3 to 21.7.

Moonshot AI · Meta · Updated for 2026

Which is better?

Muse Spark 1.3 leads the overall LLM Stats Score 55.3 to 21.7, ranking #5 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Kimi K2-Instruct-0905

  • you need open weights you can self-host or fine-tune

Choose Muse Spark 1.3

  • overall performance matters — it scores 55.3 and ranks #5 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

Kimi K2-Instruct-0905
Moonshot AI
Muse Spark 1.3
Meta
Core performance indexes
LLM Stats Score
21.7
#176
55.3
#5
Reasoning
22.0
#164
52.8
#7
Coding
10.0
#160
41.7
#10
Agents
-4.2
#169
40.4
#4
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.10 / M
Output price
— / M
$0.20 / M
Context window
—
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Kimi K2-Instruct-0905
Muse Spark 1.3
Tool use
7.4#135
35.5#2
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

29 reported for Kimi K2-Instruct-0905 · 11 for Muse Spark 1.3

No common benchmarks found

Kimi K2-Instruct-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

Context Window

Maximum input and output token capacity

Only Muse Spark 1.3 specifies input context (1,048,576 tokens). Only Muse Spark 1.3 specifies output context (943,718 tokens).

Moonshot AI
Kimi K2-Instruct-0905
Input- tokens
Output- tokens
Meta
Muse Spark 1.3
Input1,048,576 tokens
Output943,718 tokens
Fri Sep 04 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Muse Spark 1.3 supports multimodal inputs, whereas Kimi K2-Instruct-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-Instruct-0905

Text
Images
Audio
Video

Muse Spark 1.3

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2-Instruct-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.

Kimi K2-Instruct-0905

MIT

Open weights

Muse Spark 1.3

Proprietary

Closed source

Release Timeline

When each model was launched

Kimi K2-Instruct-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-Instruct-0905.

Kimi K2-Instruct-0905

Sep 5, 2025

12 months ago

Muse Spark 1.3

Sep 2, 2026

1 days ago

12mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Kimi K2-Instruct-0905 and Muse Spark 1.3 side-by-side, then vote on the output you prefer.

Kimi K2-Instruct-0905
✓ Preferred
Muse Spark 1.3
Open in Playground

FAQ

Common questions about Kimi K2-Instruct-0905 vs Muse Spark 1.3.

Which is better, Kimi K2-Instruct-0905 or Muse Spark 1.3?

Muse Spark 1.3 leads the LLM Stats Score 55.3 to 21.7. Kimi K2-Instruct-0905 is made by Moonshot AI and Muse Spark 1.3 is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Kimi K2-Instruct-0905 compare to Muse Spark 1.3 in benchmarks?

Kimi K2-Instruct-0905 scores MATH-500: 97.4%, MMLU-Redux: 92.7%, IFEval: 89.8%, AutoLogi: 89.5%, MMLU: 89.5%. Muse Spark 1.3 scores MRCR v2 (8-needle): 98.5%, MRCR v2 (8-needle, 512K-1M): 98.1%, DeepSearchQA: 89.4%, Terminal-Bench 2.1: 88.8%, DeepSWE 1.1: 75.4%.

What are the context window sizes for Kimi K2-Instruct-0905 and Muse Spark 1.3?

Kimi K2-Instruct-0905 supports an unknown number of tokens and Muse Spark 1.3 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Kimi K2-Instruct-0905 and Muse Spark 1.3?

Key differences include LLM Stats Score (21.7 vs 55.3), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K2-Instruct-0905 and Muse Spark 1.3?

Kimi K2-Instruct-0905 is developed by Moonshot AI and Muse Spark 1.3 is developed by Meta.

Related comparisons