Kimi K2-Thinking-0905 vs Qwen3 VL 4B Thinking: Specs & Benchmark Comparison
| Characteristic | Kimi K2-Thinking-0905 | Qwen3 VL 4B Thinking |
|---|---|---|
| Company | Moonshot AI | Alibaba |
| Release Date | September 4, 2025 | September 22, 2025 |
| Parameters | 1.0T | 4B |
| Multimodal | No | Yes |
| Context (input) | 262K | 262K |
| Context (output) | 66K | 262K |
| Input Price / 1M | $0.60 | $0.10 |
| Output Price / 1M | $2.40 | $1.00 |
| Average Score | 0.9 | 0.9 |
Verdict
Qwen3 VL 4B Thinking leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: Kimi K2-Thinking-0905 — 0.9, Qwen3 VL 4B Thinking — 0.9.
API Cost
Qwen3 VL 4B Thinking is 2.7x cheaper: input $0.10/1M vs $0.60/1M tokens.
Context Window
Same context size: 262K tokens.
Recency
Qwen3 VL 4B Thinking is newer: released 9/22/2025 vs 9/4/2025.
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Frequently Asked Questions
Which is better for coding — Kimi K2-Thinking-0905 or Qwen3 VL 4B Thinking?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — Kimi K2-Thinking-0905 or Qwen3 VL 4B Thinking?
Qwen3 VL 4B Thinking is cheaper for input: $0.10 per 1M tokens vs $0.60.
Which has a larger context window — Kimi K2-Thinking-0905 or Qwen3 VL 4B Thinking?
Kimi K2-Thinking-0905 supports a larger context: 262,144 tokens vs 262,144.
The Kimi K2-Thinking-0905 and Qwen3 VL 4B Thinking comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the Kimi K2-Thinking-0905 or Qwen3 VL 4B Thinking page. See also the complete list of AI model comparisons.