Last refreshed 2026-11-05. Next refresh: weekly.
Why use Vicuna 7B V1.5 on Together AI?
Together AI offers Vicuna 7B V1.5 with pay-as-you-go pricing at $0.20/1M input tokens. Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.
Setup recipe
Python + curlpip install togetherexport TOGETHER_API_KEY=...from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="lmsys/vicuna-7b-v1.5",lmsys/vicuna-7b-v1.5Request example
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="lmsys/vicuna-7b-v1.5",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "lmsys/vicuna-7b-v1.5", not the LLMReference slug "vicuna-7b-v1.5".
- Together uses "organization/model-name" format, e.g. "meta-llama/Llama-4-Scout-17B-16E-Instruct" or "Qwen/QwQ-32B". See the Together model catalog for the exact ID.
- The examples expect TOGETHER_API_KEY; rename it only if your application config maps the new variable.
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
About Vicuna 7B V1.5
Vicuna 7B V1.5, created by LMSYS, is a sophisticated language model with 7 billion parameters, rooted in the transformer architecture. It originates from fine-tuning Llama 2 using a dataset of around 125,000 user-shared conversations from ShareGPT, leveraging supervised instruction fine-tuning to boost its conversational prowess. Known for generating coherent and contextually apt responses, this model is apt for natural language processing research, machine learning, and chatbots. However, with a context limitation of 4,096 tokens, its ability to manage lengthy dialogues is somewhat constrained.