Replicate API exposes Vicuna 13B through model ID vicuna-13b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-04-19. Next refresh: weekly.
Quick Start
- 1
- 2Use the Replicate API SDK or REST API to call
vicuna-13b— see the documentation for request format. - 3
Code Examples
pip install replicateREPLICATE_API_TOKENvicuna-13bReplicate 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
# vicuna-13b format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"vicuna-13b",
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 | $0.10 |
| Output tokens | $0.50 |
Capabilities
About Vicuna 13B
Vicuna-13B is a finely-tuned open-source chatbot derived from the LLaMA model and developed with around 70,000 user-shared conversations from ShareGPT. Built on the robust Transformer architecture, it features a substantial 13-billion parameter scale. Early evaluations indicate it achieves over 90% of the effectiveness of models like OpenAI's ChatGPT and Google's Bard, surpassing other open-source models such as LLaMA and Stanford Alpaca in various scenarios. Training data includes user conversations initially captured in HTML and converted to markdown for quality filtering.