Kimi K2.5 vs Qwen3 VL 30B A3B Thinking
Kimi K2.5 leads the LLM Stats Score 39.1 to 18.3. Qwen3 VL 30B A3B Thinking is 3.0x cheaper per token.
Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Kimi K2.5 leads the overall LLM Stats Score 39.1 to 18.3, ranking #59 overall.
In the 13 individual benchmarks reported for both models, Kimi K2.5 wins 13; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 VL 30B A3B Thinking is roughly 3.0x 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 39.1 and ranks #59 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 13 of 13 exact shared results
- you process long inputs — it offers a 262,100 token context window
- you want the most recent training data — it shipped Jan 2026
Choose Qwen3 VL 30B A3B Thinking
- cost matters — it's about 3.0x cheaper per token
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 · 50 for Qwen3 VL 30B A3B Thinking
Kimi K2.5 outperforms in 13 benchmarks (AIME 2025, CharXiv-R, GPQA, InfoVQAtest, LiveCodeBench v6, LVBench, MathVision, MathVista-Mini, MMLU-Pro, MMMU-Pro, OCRBench, Video-MME, VideoMMMU), while Qwen3 VL 30B A3B Thinking is better at 0 benchmarks.
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 3.0x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).
For output processing, Kimi K2.5 ($3.00/1M tokens) is 3.0x more expensive than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).
In conclusion, Kimi K2.5 is more expensive than Qwen3 VL 30B A3B Thinking.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2.5 has 969.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 3125.8% larger.
Context Window
Maximum input and output token capacity
Kimi K2.5 accepts 262,100 input tokens compared to Qwen3 VL 30B A3B Thinking's 131,072 tokens. Kimi K2.5 can generate longer responses up to 262,100 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Both Kimi K2.5 and Qwen3 VL 30B A3B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Kimi K2.5
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
Kimi K2.5 is licensed under MIT, while Qwen3 VL 30B A3B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Kimi K2.5 was released on 2026-01-27, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Kimi K2.5 is 4 months newer than Qwen3 VL 30B A3B Thinking.
Jan 27, 2026
7 months ago
4mo newerSep 22, 2025
11 months ago
Knowledge 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 VL 30B A3B Thinking is available from Novita, DeepInfra.
Kimi K2.5
Qwen3 VL 30B A3B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2.5 and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2.5 vs Qwen3 VL 30B A3B Thinking.