Kimi K2 Base vs Qwen3 VL 30B A3B Thinking
Kimi K2 Base and Qwen3 VL 30B A3B Thinking are closely matched at 13.6 and 18.3 on the LLM Stats Score.
Moonshot AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Kimi K2 Base and Qwen3 VL 30B A3B Thinking are closely matched on the overall LLM Stats Score at 13.6 and 18.3.
In the 6 individual benchmarks reported for both models, Qwen3 VL 30B A3B Thinking 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 Kimi K2 Base
- you are already invested in the Moonshot AI ecosystem
Choose Qwen3 VL 30B A3B Thinking
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 6 exact shared results
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for Kimi K2 Base · 50 for Qwen3 VL 30B A3B Thinking
Kimi K2 Base outperforms in 2 benchmarks (MMLU, SimpleQA), while Qwen3 VL 30B A3B Thinking is better at 4 benchmarks (GPQA, LiveCodeBench v6, MMLU-Pro, SuperGPQA).
Qwen3 VL 30B A3B Thinking shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Kimi K2 Base has 969.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 3125.8% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 30B A3B Thinking specifies input context (131,072 tokens). Only Qwen3 VL 30B A3B Thinking specifies output context (32,768 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas Kimi K2 Base does not.
Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2 Base
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
Kimi K2 Base 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 Base was released on 2025-07-11, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Qwen3 VL 30B A3B Thinking is 2 months newer than Kimi K2 Base.
Jul 11, 2025
1.2 years ago
Sep 22, 2025
11 months ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against Kimi K2 Base and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Kimi K2 Base vs Qwen3 VL 30B A3B Thinking.