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llm-small · runs as qwen3.5:4b via ollama-qwen3-5-4b
Cheap, fast generalist for simple chat, short answers, classification and extraction.
Requests per day this target answered on this deployment, with the cost line.
Domains the signal layer detected on requests that ended here.
Hard stops enforced before scoring.
Pin this target with model="llm-small", or send a candidate list and let the router choose and fall back.
curl https://api.opensmartroute.ai/v1/chat/completions \
-H "Authorization: Bearer $OSR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "llm-small", "messages": [{"role": "user", "content": "Hi, how are you today?"}]}'from openai import OpenAI
client = OpenAI(base_url="https://api.opensmartroute.ai/v1", api_key="osr_live_...")
resp = client.chat.completions.create(
model="llm-small", # pin this target, or "auto" to let the router choose
messages=[{"role": "user", "content": "Hi, how are you today?"}],
extra_body={"models": ["llm-small", "auto"]}, # fall back to the router's pick if it fails
)
print(resp.model, resp.choices[0].message.content)Photo: Varun Bhatheja
Examples the similarity strategy matches against.
The catalogue prints input and output prices and what three typical monthly workloads cost on each.
Free plan, no card. Fifteen thousand decisions a month with the full trace.
