llmollama/qwen2.5-coder:7b

Code model

coder-small

Self-hosted 7B code model for quick single-file coding help - explain a snippet, a regex or an error message, write a small helper or shell one-liner, convert between languages - across 40+ programming languages; code stays inside the deployment. Repository-wide changes, refactors with tests and reviews go to the coding agent.

Executable through /v1/chat/completions On Prem boundary PII allowed

Try in playground JSON

Price per 1M tokens: $0.10; $0.0001 per 1k
Requests · 30d: 3; new
Latency: 1.3 min; measured · declared 1200 ms
Success rate: 100.0%; quality prior 0.66

Traffic over 30 days

Requests per day this target answered on this deployment, with the cost line.

requests (peak 3)
failed
cost

Tokens: 1.2K
Spend: $0.0001
Previous window: 0 req

Routed for

Domains the signal layer detected on requests that ended here.

Coding2 · 67%
Medical1 · 33%

Capabilities

DomainsCoding

ActionsCode Generation, Qa

Complexity band0.00 - 0.25

Languages*

Context window32K tokens

Streamingyes

Policy constraints

Hard stops enforced before scoring.

Data boundaryOn Prem

Regionsanywhere

PIIallowed

Max input tokensunlimited

Tenantsall

Representative prompts

Examples the similarity strategy matches against.

Explain what this regular expression matches.
Give me a one-line shell command that counts the lines in every .py file.
Convert this small bash snippet to PowerShell.
What does this Python error mean: TypeError: 'NoneType' object is not subscriptable?

Call it

Pin this target with model="coder-small", 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": "coder-small", "messages": [{"role": "user", "content": "Explain what this regular expression matches."}]}'

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="coder-small",            # pin this target, or "auto" to let the router choose
    messages=[{"role": "user", "content": "Explain what this regular expression matches."}],
    extra_body={"models": ["coder-small", "auto"]},   # fall back to the router's pick if it fails
)
print(resp.model, resp.choices[0].message.content)