# Llama: Xlam 2 70B Fc R API

Meta's Llama: Xlam 2 70B Fc R, 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 llama-xlam-2-70b-fc-r 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: llama-xlam-2-70b-fc-r
- Maker: Meta
- Context window: 128K tokens
- Input price: $2.494 per million tokens
- Output price: $2.494 per million tokens
- Providers: 1 independent provider
- Regions: us

## Providers

- [Architect](https://liquidinference.ai/providers/805445a7-0e40-4c1b-9baf-7b3b01e30e42.md): us, $2.494 input and $2.494 output per million tokens, $2.494 cache read per million tokens, 128K 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": "llama-xlam-2-70b-fc-r",
    "messages": [{"role":"user","content":"Say hello."}]
  }'
```

## Questions

### What is Llama: Xlam 2 70B Fc R?

Llama: Xlam 2 70B Fc R is a model from Meta.

### How much does Llama: Xlam 2 70B Fc R cost?

Offers now ask $2.494 per million input tokens and $2.494 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 Llama: Xlam 2 70B Fc R?

The largest offer takes 128,000 input tokens. A smaller offer can take less. The exchange skips an offer that cannot take your message.

### What can Llama: Xlam 2 70B Fc R 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 Llama: Xlam 2 70B Fc R support?

Text → Text.

### Which providers serve Llama: Xlam 2 70B Fc R?

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 Llama: Xlam 2 70B Fc R?

Send "llama-xlam-2-70b-fc-r" as the model in an OpenAI or Anthropic request. The API section links to setup steps for each client.

### When was Llama: Xlam 2 70B Fc R 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/llama-xlam-2-70b-fc-r)
- [Llama 3.2 3B Instruct](https://liquidinference.ai/models/llama-3.2-3b-instruct.md)
- [Llama 3.1 8B Instruct](https://liquidinference.ai/models/llama-3.1-8b-instruct.md)
- [Meta: Llama 3.1 8B Instruct FP8](https://liquidinference.ai/models/meta-llama-3.1-8b-instruct-fp8.md)
- [Llama: Guard 3 8B](https://liquidinference.ai/models/llama-guard-3-8b.md)
- [Llama 3 8B Instruct](https://liquidinference.ai/models/llama3-8b-instruct.md)
- [Llama: Guard 4 12B](https://liquidinference.ai/models/llama-guard-4-12b.md)
- [Set up a client](https://liquidinference.ai/connect/llama-xlam-2-70b-fc-r)
- [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)