Kimi K2 Thinking vs Qwen3 30B A3B
moonshotai/kimi-k2-thinking · qwen/qwen3-30b-a3b
As of October 31, 2026, Kimi K2 Thinking is the cheaper API on UberLLM: $0.0060 per million input tokens and $0.0250 per million output, versus $0.0517 / $0.2152 for Qwen3 30B A3B, about 88% less when output is 3 tokens for every input token. These are the median prices buyers paid over the last 24 hours. Both work with one OpenAI-compatible key and UberLLM adds no fee. Choose Kimi K2 Thinking to cut cost; choose Qwen3 30B A3B when its capabilities fit your task better.
Kimi K2 Thinking vs Qwen3 30B A3B, side by side
| Spec | Kimi K2 Thinking | Qwen3 30B A3B |
|---|---|---|
| Price · input / 1M | $0.0060 | $0.0517 |
| Price · output / 1M | $0.0250 | $0.2152 |
| Context length | 256,000 | 256,000 |
| Max output tokens | 65,536 | 32,768 |
| Input modalities | text | text |
| Output modalities | text | text |
| Tools / functions | Yes | Yes |
| Reasoning | Yes | Yes |
| % off list | 99% off | 57% off |
Median prices buyers paid on UberLLM over the last 24 hours. No UberLLM fee on requests; adding credit by card costs 5.5% + $0.50. Updated October 31, 2026. A price more than 70% below list is what buyers were billed, not an error. Why so cheap?
Kimi K2 Thinking vs Qwen3 30B A3B — FAQ
Is Kimi K2 Thinking or Qwen3 30B A3B cheaper?
Kimi K2 Thinking is cheaper on a blended token mix, by about 88%. A request costs what its provider charged, UberLLM adds no fee, and every request is listed with its cost in Activity.
What's the price difference between Kimi K2 Thinking and Qwen3 30B A3B?
Kimi K2 Thinking: $0.0060 in / $0.0250 out per 1M tokens. Qwen3 30B A3B: $0.0517 in / $0.2152 out per 1M tokens. That's roughly a 88% blended difference. Prices are live; UberLLM adds no fee.
Can I use both Kimi K2 Thinking and Qwen3 30B A3B with one API?
Yes. Both are served through a single OpenAI-compatible endpoint — set the base URL to https://api.uberllm.dev/v1 and your UberLLM key, then switch between them by changing the model id. Anthropic SDKs work via https://api.uberllm.dev/v1/messages.