Kimi K2.5 vs Qwen3 Max Thinking
Kimi K2.5 leads the LLM Stats Score 38.5 to 32.6. Kimi K2.5 is 2.0x cheaper per token.
Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Kimi K2.5 leads the overall LLM Stats Score 38.5 to 32.6, ranking #80 overall.
In the 12 individual benchmarks reported for both models, Kimi K2.5 wins 10; this is a narrower head-to-head signal than the composite indexes.
On price, Kimi K2.5 is roughly 2.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K2.5 also accepts a larger context window (262,100 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 K2.5
- overall performance matters — it scores 38.5 and ranks #80 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 10 of 12 exact shared results
- cost matters — it's about 2.0x cheaper per token
- you process long inputs — it offers a 262,100 token context window
- you need open weights you can self-host or fine-tune
Choose Qwen3 Max Thinking
- you want the most recent training data — it shipped Feb 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
40 reported for Kimi K2.5 · 34 for Qwen3 Max Thinking
Kimi K2.5 outperforms in 10 benchmarks (AA-LCR, BrowseComp, GPQA, LongBench v2, MMLU-Pro, Seal-0, SWE-bench Multilingual, SWE-Bench Verified, Terminal-Bench 2.0, WideSearch), while Qwen3 Max Thinking is better at 2 benchmarks (IMO-AnswerBench, LiveCodeBench v6).
Kimi K2.5 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 K2.5 ($0.60/1M tokens) is 2.0x cheaper than Qwen3 Max Thinking ($1.20/1M tokens).
For output processing, Kimi K2.5 ($3.00/1M tokens) is 2.0x cheaper than Qwen3 Max Thinking ($6.00/1M tokens).
In conclusion, Qwen3 Max Thinking is more expensive than Kimi K2.5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 Max Thinking has 0.0B more parameters than Kimi K2.5, making it 0.0% larger.
Context Window
Maximum input and output token capacity
Kimi K2.5 accepts 262,100 input tokens compared to Qwen3 Max Thinking's 256,000 tokens. Kimi K2.5 can generate longer responses up to 262,100 tokens, while Qwen3 Max Thinking is limited to 256,000 tokens.
Input capabilities
Documented input modalities across available providers
Kimi K2.5 supports multimodal inputs, whereas Qwen3 Max Thinking does not.
Kimi K2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2.5
Qwen3 Max Thinking
License
Usage and distribution terms
Kimi K2.5 is licensed under MIT, while Qwen3 Max Thinking uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Kimi K2.5 was released on 2026-01-27, while Qwen3 Max Thinking was released on 2026-02-13.
Qwen3 Max Thinking is 1 month newer than Kimi K2.5.
Jan 27, 2026
8 months ago
Feb 13, 2026
8 months ago
2w 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 K2.5 is available from Fireworks, Moonshot AI. Qwen3 Max Thinking is available from DeepInfra.
Kimi K2.5
Qwen3 Max Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.5 and Qwen3 Max Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.5 vs Qwen3 Max Thinking.