Kimi K3 is Kimi’s flagship model for long-horizon coding and end-to-end knowledge work, with a 1M-token context window and industry-leading intelligence.
kimi-k3 vs qwen3.7-flash
Output tokens cost $15.00 per million on kimi-k3 and $1.13 per million on qwen3.7-flash. Input tokens cost $3.00 per million on kimi-k3 and $0.28 per million on qwen3.7-flash. Cached input tokens are billed at $0.30 per million on kimi-k3 and $0.06 per million on qwen3.7-flash. Context windows are 1,048,576 tokens on kimi-k3 and 991,000 tokens on qwen3.7-flash. First-token latency measured on AIHubMix is 6.8s on kimi-k3 and 2.1s on qwen3.7-flash. Measured output throughput is 32.2 tokens/s on kimi-k3 and 104.1 tokens/s on qwen3.7-flash.
The Qwen 3.7 series' mid-to-high cost-performance "Plus" model builds on strong text capabilities with a comprehensive upgrade to vision-language abilities, while retaining full agent capabilities in coding, tool use, and productivity workflows. Its core features are multimodal interactive hybrid agent capabilities, able to perceive real-world scenes, read screens and operate GUIs, generate code based on visual references, and provide end-to-end navigation of mobile applications.
Specs & Pricing
Prices are per million tokens. Latency and throughput are rolling averages measured on AIHubMix.
Promotional prices show the discounted rate; see each model page for promotion windows.
Usage on AIHubMix last 30 days
Daily traffic served through AIHubMix — how demand for each model is trending.
Tokens / day
Requests / day
Live Performance last 3 days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Throughput (TPS)
Latency (s)
Uptime (%)
Cost Calculator
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
Which is cheaper: kimi-k3, qwen3.7-flash?
qwen3.7-flash: $1.13/M output tokens; kimi-k3: $15.00/M. Use the cost calculator above to estimate your own workload.
Which responds faster?
qwen3.7-flash: 2.1s first-token latency measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
How large is each context window?
kimi-k3 accepts 1,048,576 and qwen3.7-flash accepts 991,000 input tokens. Maximum output per request is 1,048,576 tokens on kimi-k3 and 64,000 tokens on qwen3.7-flash.
Which one generates tokens faster?
qwen3.7-flash at 104.1 tokens/s and kimi-k3 at 32.2 tokens/s, measured as output throughput on AIHubMix — a separate metric from first-token latency.
What inputs and capabilities does each model support?
kimi-k3 accepts text, image and video input and supports thinking, function calling and structured outputs; qwen3.7-flash accepts text input and supports tool calling, function calling, structured outputs, web search, long context and thinking.
Can I call kimi-k3 and qwen3.7-flash with the same API key?
Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.
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