Last refreshed 2026-06-15. Next refresh: weekly.
Why use Vicuna 13B V1.5 on Together AI?
Together AI offers Vicuna 13B V1.5 with pay-as-you-go pricing at $0.30/1M 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="vicuna-13b-v1.5",vicuna-13b-v1.5Request example
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="vicuna-13b-v1.5",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- 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 | $0.30 |
| Output tokens | $0.30 |
Capabilities
About Vicuna 13B V1.5
Vicuna 13B V1.5, developed by LMSYS, is a large language model designed for chat assistance, fine-tuned from Llama 2 using the transformer architecture. It underwent supervised instruction fine-tuning with around 125,000 conversations from ShareGPT. The model excels in text generation, conversational dialogue, and Q&A tasks, primarily intended for research. While its responses are high-quality and polite, it may lack domain-specific insights, exhibit limited contextual understanding, and display inherited biases. Quantized versions of the model provide trade-offs between size, speed, and accuracy 129.