The AI arena is free today

Open Superagent

LongCat-Flash-Thinking-2601 vs Qwen3.8-Flash-Next

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

Meituan · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

LongCat-Flash-Thinking-2601 outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 2 benchmarks (GPQA, Humanity's Last Exam). Qwen3.8-Flash-Next significantly outperforms across most benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose LongCat-Flash-Thinking-2601

  • you want predictable pricing at $0.30/M input and $1.20/M output

Choose Qwen3.8-Flash-Next

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

LongCat-Flash-Thinking-2601
Meituan
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Benchmark wins
0 of 2
2 of 2
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
128,000
—
Released
Jan 2026
Aug 2026
License
MIT
Qwen Community License 1.0

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

LongCat-Flash-Thinking-2601 outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 2 benchmarks (GPQA, Humanity's Last Exam).

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

Thu Aug 27 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

435.0B diff

LongCat-Flash-Thinking-2601 has 435.0B more parameters than Qwen3.8-Flash-Next, making it 348.0% larger.

Meituan
LongCat-Flash-Thinking-2601
560.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
560.0B
LongCat-Flash-Thinking-2601
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only LongCat-Flash-Thinking-2601 specifies input context (128,000 tokens). Only LongCat-Flash-Thinking-2601 specifies output context (128,000 tokens).

Meituan
LongCat-Flash-Thinking-2601
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Thu Aug 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.8-Flash-Next supports multimodal inputs, whereas LongCat-Flash-Thinking-2601 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-Thinking-2601

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Thinking-2601 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-Thinking-2601

MIT

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

LongCat-Flash-Thinking-2601 was released on 2026-01-14, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 7 months newer than LongCat-Flash-Thinking-2601.

LongCat-Flash-Thinking-2601

Jan 14, 2026

7 months ago

Qwen3.8-Flash-Next

Aug 26, 2026

0 days ago

7mo 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-Thinking-2601 and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

LongCat-Flash-Thinking-2601
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about LongCat-Flash-Thinking-2601 vs Qwen3.8-Flash-Next.

Which is better, LongCat-Flash-Thinking-2601 or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next significantly outperforms across most benchmarks. LongCat-Flash-Thinking-2601 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 benchmark scores, pricing, and capabilities above.

How does LongCat-Flash-Thinking-2601 compare to Qwen3.8-Flash-Next in benchmarks?

LongCat-Flash-Thinking-2601 scores AIME 2025: 99.6%, Tau2 Telecom: 99.3%, Tau2 Retail: 88.6%, LiveCodeBench: 82.8%, GPQA: 80.5%. 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-Thinking-2601 and Qwen3.8-Flash-Next?

LongCat-Flash-Thinking-2601 supports 128K 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-Thinking-2601 and Qwen3.8-Flash-Next?

Key differences include 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-Thinking-2601 and Qwen3.8-Flash-Next?

LongCat-Flash-Thinking-2601 is developed by Meituan and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

Related comparisons