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LongCat-Flash-Lite vs Qwen3.8-Flash-Next

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 19.1.

Meituan · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8-Flash-Next leads the overall LLM Stats Score 50.5 to 19.1, ranking #14 overall.

In the 2 individual benchmarks reported for both models, Qwen3.8-Flash-Next wins 2; this is a narrower head-to-head signal than the composite indexes.

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

Choose LongCat-Flash-Lite

  • you want predictable pricing at $0.10/M input and $0.40/M output

Choose Qwen3.8-Flash-Next

  • overall performance matters — it scores 50.5 and ranks #14 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

LongCat-Flash-Lite
Meituan
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
19.1
#190
50.5
#14
Reasoning
19.3
#184
50.6
#12
Coding
7.5
#170
38.4
#19
Agents
4.5
#142
37.2
#12
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
$0.10 / M
— / M
Output price
$0.40 / M
— / M
Context window
256,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
LongCat-Flash-Lite
Qwen3.8-Flash-Next
Math
17.6#182
33.3#50
Tool use
10.8#112
32.3#8
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

13 reported for LongCat-Flash-Lite · 22 for Qwen3.8-Flash-Next

2 shared

LongCat-Flash-Lite outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 2 benchmarks (GPQA, SWE-bench Multilingual).

Qwen3.8-Flash-Next significantly outperforms across most benchmarks.

Sat Aug 29 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

56.5B diff

Qwen3.8-Flash-Next has 56.5B more parameters than LongCat-Flash-Lite, making it 82.5% larger.

Meituan
LongCat-Flash-Lite
68.5Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
68.5B
LongCat-Flash-Lite
125.0B
Qwen3.8-Flash-Next

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
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Sat Aug 29 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3.8-Flash-Next supports multimodal inputs, whereas LongCat-Flash-Lite does not.

Qwen3.8-Flash-Next can handle both text and other forms of data like images, making it suitable for multimodal applications.

LongCat-Flash-Lite

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Lite is licensed under MIT, while Qwen3.8-Flash-Next uses Qwen Community License 1.0.

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

LongCat-Flash-Lite

MIT

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

LongCat-Flash-Lite was released on 2026-02-05, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 7 months newer than LongCat-Flash-Lite.

LongCat-Flash-Lite

Feb 5, 2026

6 months ago

Qwen3.8-Flash-Next

Aug 26, 2026

2 days ago

6mo 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 LongCat-Flash-Lite and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

LongCat-Flash-Lite
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about LongCat-Flash-Lite vs Qwen3.8-Flash-Next.

Which is better, LongCat-Flash-Lite or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next leads the LLM Stats Score 50.5 to 19.1. LongCat-Flash-Lite is made by Meituan and Qwen3.8-Flash-Next is made by Alibaba Cloud / Qwen Team. 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 Qwen3.8-Flash-Next in benchmarks?

LongCat-Flash-Lite scores MATH-500: 96.8%, MMLU: 85.5%, CMMLU: 82.5%, MMLU-Pro: 78.3%, Tau2 Retail: 73.1%. Qwen3.8-Flash-Next scores MathVision: 95.7%, LiveCodeBench v6: 91.9%, GPQA: 91.7%, CharXiv-R: 90.6%, RealWorldQA: 88.5%.

What are the context window sizes for LongCat-Flash-Lite and Qwen3.8-Flash-Next?

LongCat-Flash-Lite supports 256K tokens and Qwen3.8-Flash-Next 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 Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (19.1 vs 50.5), multimodal support (no vs yes), licensing (MIT vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes LongCat-Flash-Lite and Qwen3.8-Flash-Next?

LongCat-Flash-Lite is developed by Meituan and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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