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Kimi K2.6 vs Qwen3.8-Flash-Next

Qwen3.8-Flash-Next leads the LLM Stats Score 49.7 to 44.0.

Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3.8-Flash-Next leads the overall LLM Stats Score 49.7 to 44.0, ranking #15 overall.

In the 8 individual benchmarks reported for both models, Qwen3.8-Flash-Next wins 7; 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 Kimi K2.6

  • you want predictable pricing at $0.75/M input and $3.50/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 agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 7 of 8 exact shared results
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Kimi K2.6
Moonshot AI
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
44.0
#31
49.7
#15
Reasoning
44.2
#32
49.3
#15
Coding
33.8
#28
36.6
#18
Agents
26.8
#38
35.5
#13
Cost, coverage & limits
Benchmark wins
1 of 8
7 of 8
Input price
$0.75 / M
— / M
Output price
$3.50 / M
— / M
Context window
262,144
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

4 shared
Index
Kimi K2.6
Qwen3.8-Flash-Next
Math
36.8#33
32.7#53
Vision
29.0#29
34.4#12
Tool use
21.8#47
31.6#9
Multimodal
31.6#21
36.2#7
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

28 reported for Kimi K2.6 · 22 for Qwen3.8-Flash-Next

8 shared

Kimi K2.6 outperforms in 1 benchmarks (Humanity's Last Exam), while Qwen3.8-Flash-Next is better at 7 benchmarks (CharXiv-R, GPQA, LiveCodeBench v6, MathVision, SWE-bench Multilingual, SWE-Bench Pro, Toolathlon).

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

875.0B diff

Kimi K2.6 has 875.0B more parameters than Qwen3.8-Flash-Next, making it 700.0% larger.

Moonshot AI
Kimi K2.6
1.0Tparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
1000.0B
Kimi K2.6
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only Kimi K2.6 specifies input context (262,144 tokens). Only Kimi K2.6 specifies output context (131,072 tokens).

Moonshot AI
Kimi K2.6
Input262,144 tokens
Output131,072 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

Both Kimi K2.6 and Qwen3.8-Flash-Next support multimodal inputs.

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

Kimi K2.6

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2.6 is licensed under Modified MIT License, 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.

Kimi K2.6

Modified MIT License

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

Kimi K2.6 was released on 2026-04-20, while Qwen3.8-Flash-Next was released on 2026-08-26.

Qwen3.8-Flash-Next is 4 months newer than Kimi K2.6.

Kimi K2.6

Apr 20, 2026

4 months ago

Qwen3.8-Flash-Next

Aug 26, 2026

5 days ago

4mo 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 Kimi K2.6 and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

Kimi K2.6
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about Kimi K2.6 vs Qwen3.8-Flash-Next.

Which is better, Kimi K2.6 or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next leads the LLM Stats Score 49.7 to 44.0. Kimi K2.6 is made by Moonshot AI 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 Kimi K2.6 compare to Qwen3.8-Flash-Next in benchmarks?

Kimi K2.6 scores V*: 96.9%, AIME 2026: 96.4%, MathVision: 93.2%, HMMT Feb 26: 92.7%, GPQA: 90.5%. 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 Kimi K2.6 and Qwen3.8-Flash-Next?

Kimi K2.6 supports 262K 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 Kimi K2.6 and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (44.0 vs 49.7), licensing (Modified MIT License vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K2.6 and Qwen3.8-Flash-Next?

Kimi K2.6 is developed by Moonshot AI and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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