Using Llama 2 7B Chat on Replicate API
Implementation guide · Llama 2 · AI at Meta
Replicate API exposes Llama 2 7B Chat through model ID meta/llama-2-7b-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
- 2Use the Replicate API SDK or REST API to call
meta/llama-2-7b-chat— see the documentation for request format. - 3
Code Examples
pip install replicateREPLICATE_API_TOKENmeta/llama-2-7b-chatReplicate 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-2-7b-chat format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"meta/llama-2-7b-chat",
input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))Pricing on Replicate API
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.05 |
| Output tokens | $0.25 |
Capabilities
About Llama 2 7B Chat
The Llama 2 7B Chat model is a fine-tuned variant of Meta's Llama 2 series, optimized for conversational AI applications. Built on an auto-regressive transformer architecture, it boasts 7 billion parameters and has been trained on a diverse dataset of 2 trillion tokens. The model underwent supervised fine-tuning and reinforcement learning with human feedback to enhance its performance in dialogue scenarios. It demonstrates competitive capabilities in terms of helpfulness and safety compared to both open-source and closed-source alternatives like ChatGPT and PaLM.