Using Llama 2 70B Chat on Replicate API

Implementation guide · Llama 2 · AI at Meta

ServerlessOpen Weights

Replicate API exposes Llama 2 70B Chat through model ID meta/llama-2-70b-chat. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-07-09. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at Replicate API and generate an API key.
  2. 2
    Use the Replicate API SDK or REST API to call meta/llama-2-70b-chat — see the documentation for request format.
  3. 3
    You'll be billed $0.65/1M input, $2.75/1M output tokens. See full pricing.

Code Examples

Install
pip install replicate
API key
REPLICATE_API_TOKEN
Model ID
meta/llama-2-70b-chat

Replicate uses "owner/model-name" format (e.g. "meta/meta-llama-3-8b-instruct") for the latest version, or "owner/model-name:version-sha" to pin to a specific version. The REST endpoint splits owner and model-name into the path: /v1/models/{owner}/{model-name}/predictions.

import replicate

# reads REPLICATE_API_TOKEN from env
# meta/llama-2-70b-chat format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
    "meta/llama-2-70b-chat",
    input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))

Pricing on Replicate API

TypePrice (per 1M)
Input tokens$0.65
Output tokens$2.75

Capabilities

Structured Outputs

About Llama 2 70B Chat

Llama 2 70B Chat is a large-scale language model with 70 billion parameters, designed for conversational AI applications. Released on July 18, 2023, it's part of Meta's Llama 2 family, featuring advanced transformer architecture optimized through supervised fine-tuning and reinforcement learning with human feedback. The model excels in generating human-like responses, outperforming many open-source alternatives and rivaling closed-source models like ChatGPT. Trained on 2 trillion tokens from diverse public sources, it's suitable for commercial and research applications in English, particularly for assistant-like functionalities. The model is available on Hugging Face for further exploration and implementation .

Model Specs

Released2023-07-18
Parameters70B
Context4k
ArchitectureDecoder Only

Provider

Replicate API

Replicate

San Francisco, California, United States