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

Qwen3.8-Flash-Next leads the LLM Stats Score 49.7 to 20.1.

Meituan · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8-Flash-Next leads the overall LLM Stats Score 49.7 to 20.1, ranking #15 overall.

In the 1 individual benchmarks reported for both models, Qwen3.8-Flash-Next wins 1; 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-Chat

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

Choose Qwen3.8-Flash-Next

  • overall performance matters — it scores 49.7 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

LongCat-Flash-Chat
Meituan
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
20.1
#183
49.7
#15
Reasoning
20.0
#179
49.3
#15
Coding
12.6
#132
36.6
#18
Agents
9.4
#115
35.5
#13
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
128,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
LongCat-Flash-Chat
Qwen3.8-Flash-Next
Math
19.2#162
32.7#54
Tool use
9.7#123
31.6#9
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for LongCat-Flash-Chat · 22 for Qwen3.8-Flash-Next

1 shared

LongCat-Flash-Chat outperforms in 0 benchmarks, while Qwen3.8-Flash-Next is better at 1 benchmark (GPQA).

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

Mon Aug 31 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

435.0B diff

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

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

Context Window

Maximum input and output token capacity

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

Meituan
LongCat-Flash-Chat
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Mon Aug 31 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

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

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Chat 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-Chat

MIT

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

LongCat-Flash-Chat was released on 2025-08-29, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 12 months newer than LongCat-Flash-Chat.

LongCat-Flash-Chat

Aug 29, 2025

1.0 years ago

Qwen3.8-Flash-Next

Aug 26, 2026

4 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 LongCat-Flash-Chat and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

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

FAQ

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

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

Qwen3.8-Flash-Next leads the LLM Stats Score 49.7 to 20.1. LongCat-Flash-Chat 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-Chat compare to Qwen3.8-Flash-Next in benchmarks?

LongCat-Flash-Chat scores MATH-500: 96.4%, MMLU: 89.7%, IFEval: 89.6%, ZebraLogic: 89.3%, HumanEval: 88.4%. 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-Chat and Qwen3.8-Flash-Next?

LongCat-Flash-Chat 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-Chat and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (20.1 vs 49.7), 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-Chat and Qwen3.8-Flash-Next?

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

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