Kimi K2-Thinking-0905 vs Qwen3 VL 4B Instruct: Specs & Benchmark Comparison
| Characteristic | Kimi K2-Thinking-0905 | Qwen3 VL 4B Instruct |
|---|---|---|
| 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 | $0.60 |
| Average Score | 0.9 | 0.9 |
Verdict
Qwen3 VL 4B Instruct 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 Instruct — 0.9.
API Cost
Qwen3 VL 4B Instruct is 4.3x cheaper: input $0.10/1M vs $0.60/1M tokens.
Context Window
Same context size: 262K tokens.
Recency
Qwen3 VL 4B Instruct 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 Instruct?
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 Instruct?
Qwen3 VL 4B Instruct 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 Instruct?
Kimi K2-Thinking-0905 supports a larger context: 262,144 tokens vs 262,144.
The Kimi K2-Thinking-0905 and Qwen3 VL 4B Instruct 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 Instruct page. See also the complete list of AI model comparisons.