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Kimi-k1.5 vs Qwen3 VL 30B A3B Thinking

Kimi-k1.5 and Qwen3 VL 30B A3B Thinking are closely matched at 17.3 and 18.3 on the LLM Stats Score.

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

Which is better?

Kimi-k1.5 and Qwen3 VL 30B A3B Thinking are closely matched on the overall LLM Stats Score at 17.3 and 18.3.

The models split the 2 individual benchmarks reported for both models evenly.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Kimi-k1.5

  • you are already invested in the Moonshot AI ecosystem

Choose Qwen3 VL 30B A3B Thinking

  • you want the most recent training data — it shipped Sep 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
17.3
#206
18.3
#203
16.5
#204
19.5
#189
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
— / M
$0.20 / M
Output price
— / M
$0.99 / M
Context window
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Kimi-k1.5
Qwen3 VL 30B A3B Thinking
20.5#150
22.5#130
11.5#106
12.8#98
15.3#86
15.7#85
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for Kimi-k1.5 · 50 for Qwen3 VL 30B A3B Thinking

2 shared

Kimi-k1.5 outperforms in 1 benchmarks (IFEval), while Qwen3 VL 30B A3B Thinking is better at 1 benchmark (MMLU).

Both models are evenly matched across the benchmarks.

Tue Sep 08 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

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).

Moonshot AI
Kimi-k1.5
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Tue Sep 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Kimi-k1.5 and Qwen3 VL 30B A3B Thinking support multimodal inputs.

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

Kimi-k1.5

Text
Images
Audio
Video

Qwen3 VL 30B A3B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi-k1.5 is licensed under a proprietary license, 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.

Kimi-k1.5

Proprietary

Closed source

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi-k1.5 was released on 2025-01-20, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.

Qwen3 VL 30B A3B Thinking is 8 months newer than Kimi-k1.5.

Kimi-k1.5

Jan 20, 2025

1.6 years ago

Qwen3 VL 30B A3B Thinking

Sep 22, 2025

11 months ago

8mo 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-k1.5 and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.

Kimi-k1.5
✓ Preferred
Qwen3 VL 30B A3B Thinking
Open in Playground

FAQ

Common questions about Kimi-k1.5 vs Qwen3 VL 30B A3B Thinking.

Which is better, Kimi-k1.5 or Qwen3 VL 30B A3B Thinking?

Kimi-k1.5 and Qwen3 VL 30B A3B Thinking are closely matched on the LLM Stats Score at 17.3 and 18.3. Kimi-k1.5 is made by Moonshot AI and Qwen3 VL 30B A3B Thinking 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-k1.5 compare to Qwen3 VL 30B A3B Thinking in benchmarks?

Kimi-k1.5 scores MATH-500: 96.2%, CLUEWSC: 91.4%, C-Eval: 88.3%, MMLU: 87.4%, IFEval: 87.2%. Qwen3 VL 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%.

What are the context window sizes for Kimi-k1.5 and Qwen3 VL 30B A3B Thinking?

Kimi-k1.5 supports an unknown number of tokens and Qwen3 VL 30B A3B Thinking supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Kimi-k1.5 and Qwen3 VL 30B A3B Thinking?

Key differences include LLM Stats Score (17.3 vs 18.3), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi-k1.5 and Qwen3 VL 30B A3B Thinking?

Kimi-k1.5 is developed by Moonshot AI and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.