# Kimi K2 Instruct FP4 API

Moonshot's Kimi K2 Instruct FP4, through an OpenAI-compatible API. Providers quote it on an open exchange, and each request goes to the offer with the lowest estimated charge that meets your rules.

- Providers compete for each request. The exchange ranks the offers that meet your rules by estimated charge. It fixes your maximum charge before the first token, and you pay for the tokens that the model uses.
- The OpenAI and Anthropic APIs. Use the OpenAI or Anthropic SDK that you have. Set the base URL and your key, and send kimi-k2-instruct-fp4 as the model.
- Your data rules. Send x-liquid-retention: none and only offers whose provider does not keep your content compete for the request.

## Facts

- Model name: kimi-k2-instruct-fp4
- Maker: Moonshot
- Context window: 131.1K tokens
- Input price: $0.400 per million tokens
- Output price: $1.798 per million tokens
- Providers: 1 independent provider
- Regions: us

## Providers

- [Architect](https://liquidinference.ai/providers/805445a7-0e40-4c1b-9baf-7b3b01e30e42.md): us, $0.400 input and $1.798 output per million tokens, $0.400 cache read per million tokens, 131.1K tokens of context

## Request

```sh
curl https://router.inference.ai.exchange/v1/chat/completions \
  -H "Authorization: Bearer $LIQUID_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k2-instruct-fp4",
    "messages": [{"role":"user","content":"Say hello."}]
  }'
```

## Questions

### What is Kimi K2 Instruct FP4?

Kimi K2 Instruct FP4 is a model from Moonshot.

### How much does Kimi K2 Instruct FP4 cost?

Offers now ask $0.400 per million input tokens and $1.798 per million output tokens. A job pays for the tokens it uses. The exchange picks the cheapest eligible offer.

### What is the context length of Kimi K2 Instruct FP4?

The largest offer takes 131,072 input tokens. A smaller offer can take less. The exchange skips an offer that cannot take your message.

### What can Kimi K2 Instruct FP4 do?

Its providers list Reasoning effort, JSON object, JSON schema, Frequency penalty, Logit bias, Log probabilities, Min-p sampling, Presence penalty, Repetition penalty, Seed, Stop sequences, Top-k sampling, Top-p sampling, Text, Tools.

### What inputs and outputs does Kimi K2 Instruct FP4 support?

Text → Text.

### Which providers serve Kimi K2 Instruct FP4?

1 independent provider quote it now, with 1 offer. The table above ranks them by the cost of a typical job.

### How do I call Kimi K2 Instruct FP4?

Send "kimi-k2-instruct-fp4" as the model in an OpenAI or Anthropic request. The API section links to setup steps for each client.

### When was Kimi K2 Instruct FP4 listed?

The exchange first listed it on 10/10/2026. This is not its release date.

## Related pages

- [This page in a browser](https://liquidinference.ai/models/kimi-k2-instruct-fp4)
- [Kimi K3](https://liquidinference.ai/models/kimi-k3.md)
- [Kimi k2.6:thinking](https://liquidinference.ai/models/kimi-k2.6%3Athinking.md)
- [Kimi K2 Instruct 0905](https://liquidinference.ai/models/kimi-k2-instruct-0905.md)
- [Kimi K2 Instruct](https://liquidinference.ai/models/kimi-k2-instruct.md)
- [Kimi K2 Instruct Fast](https://liquidinference.ai/models/kimi-k2-instruct-fast.md)
- [Kimi K2 Instruct 0711](https://liquidinference.ai/models/kimi-k2-instruct-0711.md)
- [Set up a client](https://liquidinference.ai/connect/kimi-k2-instruct-fp4)
- [All models](https://liquidinference.ai/models)
- [Providers](https://liquidinference.ai/providers.md)
- [Discover the best model for your budget](https://liquidinference.ai/discover)
- [Quickstart](https://liquidinference.ai/docs/quickstart.md)
- [llms.txt: the index of every page, as Markdown](https://liquidinference.ai/llms.txt)
- [llms-full.txt: every page in one file](https://liquidinference.ai/llms-full.txt)