Kimi K2.6 vs Qwen3.8 Flash
Qwen3.8 Flash leads the LLM Stats Score 49.6 to 44.0. Qwen3.8 Flash is 6.3x cheaper per token.
Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3.8 Flash leads the overall LLM Stats Score 49.6 to 44.0, ranking #16 overall.
In the 8 individual benchmarks reported for both models, Qwen3.8 Flash wins 7; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3.8 Flash is roughly 6.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.8 Flash also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Kimi K2.6
- you need open weights you can self-host or fine-tune
Choose Qwen3.8 Flash
- overall performance matters — it scores 49.6 and ranks #16 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
- cost matters — it's about 6.3x cheaper per token
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
28 reported for Kimi K2.6 · 22 for Qwen3.8 Flash
Kimi K2.6 outperforms in 1 benchmarks (Humanity's Last Exam), while Qwen3.8 Flash is better at 7 benchmarks (CharXiv-R, GPQA, LiveCodeBench v6, MathVision, SWE-bench Multilingual, SWE-Bench Pro, Toolathlon).
Qwen3.8 Flash significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2.6 ($0.75/1M tokens) is 5.0x more expensive than Qwen3.8 Flash ($0.15/1M tokens).
For output processing, Kimi K2.6 ($3.50/1M tokens) is 7.4x more expensive than Qwen3.8 Flash ($0.47/1M tokens).
In conclusion, Kimi K2.6 is more expensive than Qwen3.8 Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2.6 has 875.0B more parameters than Qwen3.8 Flash, making it 700.0% larger.
Context Window
Maximum input and output token capacity
Qwen3.8 Flash accepts 1,000,000 input tokens compared to Kimi K2.6's 262,144 tokens. Both models can generate responses up to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Kimi K2.6 and Qwen3.8 Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Kimi K2.6
Qwen3.8 Flash
License
Usage and distribution terms
Kimi K2.6 is licensed under Modified MIT License, while Qwen3.8 Flash uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Modified MIT License
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Kimi K2.6 was released on 2026-04-20, while Qwen3.8 Flash was released on 2026-08-26.
Qwen3.8 Flash is 4 months newer than Kimi K2.6.
Apr 20, 2026
4 months ago
Aug 26, 2026
5 days ago
4mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Kimi K2.6 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together. Qwen3.8 Flash is available from Novita.
Kimi K2.6
Qwen3.8 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.6 and Qwen3.8 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.6 vs Qwen3.8 Flash.