Kimi K3 API Pricing
Moonshot AI · released Jul 16, 2026 · 1.05M context · API model ID kimi-k3
Kimi K3 by Moonshot AI API pricing: $3.00 per 1M input tokens and $15.00 per 1M output tokens (provider list price via models.dev, Oct 10, 2026).
Prices
| Price | USD per 1M tokens |
|---|---|
| Input | $3.00 |
| Output | $15.00 |
| Cache read | $0.30 |
| Cache write | $3.00 |
Moonshot AI's list price for its own API, as compiled by models.dev and checked Oct 10, 2026, 09:00 UTC. Prices on cloud platforms and resellers can differ. Provider documentation
Estimated monthly cost
$3,150
per month
- per day
- $105.00
- per request
- $0.0105
Cannot estimate: a needed price is not published.
Cost = input tokens × input price + output tokens × output price, 30 days a month. Cached input uses the cache read price. Cache write fees are not included.
Monthly cost by workload
| Workload | Per month |
|---|---|
| Chatbot1,000 in / 500 out tokens, 10,000 requests a day | $3,150/mo |
| RAG8,000 in / 500 out tokens, 5,000 requests a day | $4,725/mo |
| Coding agent50,000 in / 2,000 out tokens, 1,000 requests a day, 80% cached input | $2,160/mo |
Context and capabilities
- Context
- 1,048,576 tokens
- Max output
- 1,048,576 tokens
- Input
- text, image, video
- Output
- text
- Knowledge cutoff
- Not published
- Open weights
- Yes
- Tool calling
- Yes
- Reasoning
- Yes
- Structured outputs
- Yes
Capabilities and limits as listed by models.dev.
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Price history
No price changes since we started tracking on Oct 8, 2026.
Questions
- How much does Kimi K3 cost per month?
- For a chatbot handling 10,000 requests a day with 1,000 input and 500 output tokens each, Kimi K3 costs about $3,150 per month at Moonshot AI's list prices ($3.00 per 1M input tokens, $15.00 per 1M output tokens).
- Does Kimi K3 support prompt caching?
- Yes. Cached input costs $0.30 per 1M tokens, compared with $3.00 for regular input. Writing to the cache costs $3.00 per 1M tokens.
- How long is Kimi K3's context window?
- Kimi K3 accepts up to 1,048,576 tokens (1.05M) of context and returns up to 1,048,576 tokens per response.