Last refreshed 2026-04-19. Next refresh: weekly.
Why use Vicuna 13B on Replicate API?
Replicate API offers Vicuna 13B with pay-as-you-go pricing at $0.10/1M input tokens. Replicate is a cloud-based platform that enables users to run machine learning models easily and efficiently.
Compare Vicuna 13B across 2 providers to find the best fit for your use caseSetup recipe
Python + curlpip install replicateexport REPLICATE_API_TOKEN=...import replicate
output = replicate.run(
"vicuna-13b",
input={"prompt": "Hello"}vicuna-13bRequest example
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))Gotchas
- 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.
- The examples expect REPLICATE_API_TOKEN; rename it only if your application config maps the new variable.
Compare Vicuna 13B Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| GCP Vertex AI | — | — |
| Replicate API | $0.10 | $0.50 |
Pricing
| 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.