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LongCat-2.5 vs Qwen3.8-Flash-Next

LongCat-2.5 and Qwen3.8-Flash-Next are closely matched at 50.0 and 47.8 on the LLM Stats Score.

Meituan · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

LongCat-2.5 and Qwen3.8-Flash-Next are closely matched on the overall LLM Stats Score at 50.0 and 47.8.

In the 5 individual benchmarks reported for both models, LongCat-2.5 wins 4; 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-2.5

  • you value its reported benchmark strengths — it wins 4 of 5 exact shared results
  • you want the most recent training data — it shipped Nov 2026

Choose Qwen3.8-Flash-Next

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

At a glance

The differences that matter most.

LongCat-2.5
Meituan
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
50.0
#20
47.8
#35
Reasoning
48.3
#21
48.2
#22
Coding
38.6
#27
33.5
#48
Agents
36.3
#23
32.9
#40
Cost, coverage & limits
Benchmark wins
4 of 5
1 of 5
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

5 shared
Index
LongCat-2.5
Qwen3.8-Flash-Next
Math
37.2#37
32.5#64
Vision
32.5#29
34.0#19
Tool use
30.2#15
30.1#16
Multimodal
34.8#15
34.8#16
Productivity
13.1#11
14.5#6
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

23 reported for LongCat-2.5 · 22 for Qwen3.8-Flash-Next

5 shared

LongCat-2.5 outperforms in 4 benchmarks (DeepSWE 1.1, MathVision, NL2Repo, Vision2Web), while Qwen3.8-Flash-Next is better at 1 benchmark (CharXiv-R).

LongCat-2.5 significantly outperforms across most benchmarks.

Mon Nov 02 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1475.0B diff

LongCat-2.5 has 1475.0B more parameters than Qwen3.8-Flash-Next, making it 1180.0% larger.

Meituan
LongCat-2.5
1.6Tparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
1600.0B
LongCat-2.5
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only LongCat-2.5 specifies input context (1,048,576 tokens). Only LongCat-2.5 specifies output context (131,072 tokens).

Meituan
LongCat-2.5
Input1,048,576 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Mon Nov 02 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both LongCat-2.5 and Qwen3.8-Flash-Next support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

LongCat-2.5

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

Release Timeline

When each model was launched

LongCat-2.5 was released on 2026-11-01, while Qwen3.8-Flash-Next was released on 2026-08-26.

LongCat-2.5 is 2 months newer than Qwen3.8-Flash-Next.

LongCat-2.5

Nov 1, 2026

0 days ago

2mo newer
Qwen3.8-Flash-Next

Aug 26, 2026

2 months ago

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-2.5 and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

LongCat-2.5
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about LongCat-2.5 vs Qwen3.8-Flash-Next.

Which is better, LongCat-2.5 or Qwen3.8-Flash-Next?

LongCat-2.5 and Qwen3.8-Flash-Next are closely matched on the LLM Stats Score at 50.0 and 47.8. LongCat-2.5 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-2.5 compare to Qwen3.8-Flash-Next in benchmarks?

LongCat-2.5 scores MathVision: 96.5%, BrowseComp: 91.9%, CharXiv-R: 90.2%, Terminal-Bench 2.1: 88.4%, Video-MME: 85.2%. 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-2.5 and Qwen3.8-Flash-Next?

LongCat-2.5 supports 1.0M 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-2.5 and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (50.0 vs 47.8), licensing (Unknown vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes LongCat-2.5 and Qwen3.8-Flash-Next?

LongCat-2.5 is developed by Meituan and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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