Model Comparison
Kimi K2-Thinking-0905 vs Qwen3.5-35B-A3BWhich is better in 2026?
Kimi K2-Thinking-0905 shows notably better performance in the majority of benchmarks. Qwen3.5-35B-A3B is 1.2x cheaper per token.
Verdict: Kimi K2-Thinking-0905 vs Qwen3.5-35B-A3B — which is better?
Kimi K2-Thinking-0905 (by Moonshot AI) and Qwen3.5-35B-A3B (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Kimi K2-Thinking-0905 outperforms in 8 benchmarks (GPQA, HMMT 2025, Humanity's Last Exam, LiveCodeBench v6, MMLU-Redux, OJBench, Seal-0, SWE-Bench Verified), while Qwen3.5-35B-A3B is better at 3 benchmarks (BrowseComp, BrowseComp-zh, MMLU-Pro). Kimi K2-Thinking-0905 shows notably better performance in the majority of benchmarks.
On price, Qwen3.5-35B-A3B is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose Kimi K2-Thinking-0905 if…
- you want the strongest raw capability — it leads on 8 of 11 shared benchmarks
Choose Qwen3.5-35B-A3B if…
- cost matters — it's about 1.2x cheaper per token
- you want the most recent training data — it shipped Feb 2026
Performance Benchmarks
Comparative analysis across standard metrics
Kimi K2-Thinking-0905 outperforms in 8 benchmarks (GPQA, HMMT 2025, Humanity's Last Exam, LiveCodeBench v6, MMLU-Redux, OJBench, Seal-0, SWE-Bench Verified), while Qwen3.5-35B-A3B is better at 3 benchmarks (BrowseComp, BrowseComp-zh, MMLU-Pro).
Kimi K2-Thinking-0905 shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2-Thinking-0905 ($0.47/1M tokens) is 1.9x more expensive than Qwen3.5-35B-A3B ($0.25/1M tokens).
For output processing, Kimi K2-Thinking-0905 ($2.00/1M tokens) costs the same as Qwen3.5-35B-A3B ($2.00/1M tokens).
In conclusion, Kimi K2-Thinking-0905 is more expensive than Qwen3.5-35B-A3B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2-Thinking-0905 has 965.0B more parameters than Qwen3.5-35B-A3B, making it 2757.1% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 262,144 tokens. Kimi K2-Thinking-0905 can generate longer responses up to 262,144 tokens, while Qwen3.5-35B-A3B is limited to 65,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3.5-35B-A3B supports multimodal inputs, whereas Kimi K2-Thinking-0905 does not.
Qwen3.5-35B-A3B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Kimi K2-Thinking-0905
Qwen3.5-35B-A3B
License
Usage and distribution terms
Kimi K2-Thinking-0905 is licensed under MIT, while Qwen3.5-35B-A3B 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-Thinking-0905 was released on 2025-09-05, while Qwen3.5-35B-A3B was released on 2026-02-24.
Qwen3.5-35B-A3B is 6 months newer than Kimi K2-Thinking-0905.
Sep 5, 2025
10 months ago
Feb 24, 2026
5 months ago
5mo 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-Thinking-0905 is available from DeepInfra, Novita, Fireworks. Qwen3.5-35B-A3B is available from Novita.
Kimi K2-Thinking-0905
Qwen3.5-35B-A3B
Outputs Comparison
Key Takeaways
Kimi K2-Thinking-0905
View detailsMoonshot AI
Qwen3.5-35B-A3B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Kimi K2-Thinking-0905 and Qwen3.5-35B-A3B side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Kimi K2-Thinking-0905 vs Qwen3.5-35B-A3B.