Model Comparison

LongCat-Flash-Lite vs Muse Spark 1.1Which is better in 2026?

Comparing LongCat-Flash-Lite and Muse Spark 1.1 across benchmarks, pricing, and capabilities.

Verdict: LongCat-Flash-Lite vs Muse Spark 1.1 — which is better?

LongCat-Flash-Lite (by Meituan) and Muse Spark 1.1 (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

On price, LongCat-Flash-Lite is roughly 11.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Muse Spark 1.1 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Choose LongCat-Flash-Lite if…

  • cost matters — it's about 11.4x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose Muse Spark 1.1 if…

  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Jul 2026

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

LongCat-Flash-Lite and Muse Spark 1.1don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

LongCat-Flash-Lite costs less

For input processing, LongCat-Flash-Lite ($0.10/1M tokens) is 12.5x cheaper than Muse Spark 1.1 ($1.25/1M tokens).

For output processing, LongCat-Flash-Lite ($0.40/1M tokens) is 10.6x cheaper than Muse Spark 1.1 ($4.25/1M tokens).

In conclusion, Muse Spark 1.1 is more expensive than LongCat-Flash-Lite.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Jul 27 2026 • llm-stats.com
Meituan
LongCat-Flash-Lite
Input tokens$0.10
Output tokens$0.40
Best providerMeituan
Meta
Muse Spark 1.1
Input tokens$1.25
Output tokens$4.25
Best providerMeta
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Muse Spark 1.1 accepts 1,048,576 input tokens compared to LongCat-Flash-Lite's 256,000 tokens. Muse Spark 1.1 can generate longer responses up to 131,072 tokens, while LongCat-Flash-Lite is limited to 128,000 tokens.

Meituan
LongCat-Flash-Lite
Input256,000 tokens
Output128,000 tokens
Meta
Muse Spark 1.1
Input1,048,576 tokens
Output131,072 tokens
Mon Jul 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Muse Spark 1.1 supports multimodal inputs, whereas LongCat-Flash-Lite does not.

Muse Spark 1.1 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 Spark 1.1

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Lite is licensed under MIT, while Muse Spark 1.1 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 Spark 1.1

Proprietary

Closed source

Release Timeline

When each model was launched

LongCat-Flash-Lite was released on 2026-02-05, while Muse Spark 1.1 was released on 2026-07-09.

Muse Spark 1.1 is 5 months newer than LongCat-Flash-Lite.

LongCat-Flash-Lite

Feb 5, 2026

5 months ago

Muse Spark 1.1

Jul 9, 2026

2 weeks ago

5mo 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

Provider Availability

LongCat-Flash-Lite is available from Meituan. Muse Spark 1.1 is available from Meta Model API.

LongCat-Flash-Lite

meituan logo
Meituan
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

Muse Spark 1.1

meta logo
Meta
Input Price:Input: $1.25/1MOutput Price:Output: $4.25/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Meituan
Less expensive input tokens
Less expensive output tokens
Has open weights
Meta
Larger context window (1,048,576 tokens)
Supports multimodal inputs

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against LongCat-Flash-Lite and Muse Spark 1.1 side-by-side, then vote on the output you prefer.

LongCat-Flash-Lite
✓ Preferred
Muse Spark 1.1
Open in Playground
AI Model Comparison Table
Feature
Meituan
LongCat-Flash-Lite
Meta
Muse Spark 1.1

FAQ

Common questions about LongCat-Flash-Lite vs Muse Spark 1.1.

Which is better, LongCat-Flash-Lite or Muse Spark 1.1?

LongCat-Flash-Lite (Meituan) and Muse Spark 1.1 (Meta) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does LongCat-Flash-Lite compare to Muse Spark 1.1 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 Spark 1.1 scores CharXiv-R: 88.4%, MCP Atlas: 88.1%, OSWorld-Verified: 80.8%, Terminal-Bench 2.1: 80.0%, BabyVision: 76.3%.

Is LongCat-Flash-Lite cheaper than Muse Spark 1.1?

LongCat-Flash-Lite is 12.5x cheaper for input tokens. LongCat-Flash-Lite costs $0.10/M input and $0.40/M output via meituan. Muse Spark 1.1 costs $1.25/M input and $4.25/M output via meta.

What are the context window sizes for LongCat-Flash-Lite and Muse Spark 1.1?

LongCat-Flash-Lite supports 256K tokens and Muse Spark 1.1 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 LongCat-Flash-Lite and Muse Spark 1.1?

Key differences include context window (256K vs 1.0M), input pricing ($0.10 vs $1.25/M), 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 Spark 1.1?

LongCat-Flash-Lite is developed by Meituan and Muse Spark 1.1 is developed by Meta.

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