The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
Input $/1M
$0.10
Output $/1M
$0.32
Context
131K
Max output
16K
Released
Dec 6, 2024
Modalities
text
Intelligence index-
Coding index12
Agentic index-
Traffic over 30 days
Requests per day this target answered on this deployment, with the cost line.
requests (peak 4)
failed
cost
Tokens
212
Spend
$0.0002
Previous window
0 req
Routed for
Domains the signal layer detected on requests that ended here.
General3 · 75%
Legal1 · 25%
Capabilities
DomainsGeneral, Finance, Legal, Medical, Hr, Customer Support
Extract the account number and email from this support ticket.
Summarize this patient intake note.
Call it
Pin this target with model="llm-onprem", or send a candidate list and let the router choose and fall back.
curlbash
curl https://api.opensmartroute.ai/v1/chat/completions \
-H "Authorization: Bearer $OSR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "llm-onprem", "messages": [{"role": "user", "content": "Extract the account number and email from this support ticket."}]}'
OpenAI SDKpython
from openai import OpenAI
client = OpenAI(base_url="https://api.opensmartroute.ai/v1", api_key="osr_live_...")
resp = client.chat.completions.create(
model="llm-onprem", # pin this target, or "auto" to let the router choose
messages=[{"role": "user", "content": "Extract the account number and email from this support ticket."}],
extra_body={"models": ["llm-onprem", "auto"]}, # fall back to the router's pick if it fails
)
print(resp.model, resp.choices[0].message.content)
On-prem private model (llm-onprem) - OpenSmartRoute
