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LongCat-Flash-Lite vs Muse Wonder Full

Muse Wonder Full leads the LLM Stats Score 52.1 to 18.6.

Meituan · Meta · Updated for 2026

Which is better?

Muse Wonder Full leads the overall LLM Stats Score 52.1 to 18.6, ranking #13 overall.

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

Choose LongCat-Flash-Lite

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

Choose Muse Wonder Full

  • overall performance matters — it scores 52.1 and ranks #13 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

LongCat-Flash-Lite
Meituan
Muse Wonder Full
Meta
Core performance indexes
LLM Stats Score
18.6
#226
52.1
#13
Reasoning
18.9
#220
38.4
#71
Coding
7.0
#200
41.5
#8
Agents
4.1
#173
38.5
#8
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.10 / M
— / M
Output price
$0.40 / M
— / M
Context window
256,000
—

Individual benchmarks

13 reported for LongCat-Flash-Lite · 16 for Muse Wonder Full

No common benchmarks found

LongCat-Flash-Lite and Muse Wonder Fulldon'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 LongCat-Flash-Lite specifies input context (256,000 tokens). Only LongCat-Flash-Lite specifies output context (128,000 tokens).

Meituan
LongCat-Flash-Lite
Input256,000 tokens
Output128,000 tokens
Meta
Muse Wonder Full
Input- tokens
Output- tokens
Wed Oct 14 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Muse Wonder Full supports multimodal inputs, whereas LongCat-Flash-Lite does not.

Muse Wonder Full can handle both text and other forms of data like images, making it suitable for multimodal applications.

LongCat-Flash-Lite

Text
Images
Audio
Video

Muse Wonder Full

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Lite is licensed under MIT, while Muse Wonder Full uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

LongCat-Flash-Lite

MIT

Open weights

Muse Wonder Full

Proprietary

Closed source

Release Timeline

When each model was launched

LongCat-Flash-Lite was released on 2026-02-05, while Muse Wonder Full was released on 2026-10-12.

Muse Wonder Full is 8 months newer than LongCat-Flash-Lite.

LongCat-Flash-Lite

Feb 5, 2026

8 months ago

Muse Wonder Full

Oct 12, 2026

2 days ago

8mo 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?

Judge for yourself.

Run your own prompts against LongCat-Flash-Lite and Muse Wonder Full side-by-side, then vote on the output you prefer.

LongCat-Flash-Lite
✓ Preferred
Muse Wonder Full
Open in Playground

FAQ

Common questions about LongCat-Flash-Lite vs Muse Wonder Full.

Which is better, LongCat-Flash-Lite or Muse Wonder Full?

Muse Wonder Full leads the LLM Stats Score 52.1 to 18.6. LongCat-Flash-Lite is made by Meituan and Muse Wonder Full is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does LongCat-Flash-Lite compare to Muse Wonder Full in benchmarks?

LongCat-Flash-Lite scores MATH-500: 96.8%, MMLU: 85.5%, CMMLU: 82.5%, MMLU-Pro: 78.3%, Tau2 Retail: 73.1%. Muse Wonder Full scores MemoryBench: 85.5%, DeepSWE 1.1: 79.0%, OSWorld 2.1 (partial): 78.4%, JobBench: 75.3%, HealthBench Professional: 62.3%.

What are the context window sizes for LongCat-Flash-Lite and Muse Wonder Full?

LongCat-Flash-Lite supports 256K tokens and Muse Wonder Full supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between LongCat-Flash-Lite and Muse Wonder Full?

Key differences include LLM Stats Score (18.6 vs 52.1), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes LongCat-Flash-Lite and Muse Wonder Full?

LongCat-Flash-Lite is developed by Meituan and Muse Wonder Full is developed by Meta.

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