vLLM Endpoint

Serve Qwen Coder

Deploy a Qwen Coder model as an OpenAI-compatible vLLM endpoint — tuned for code completion, refactors, and coding-assistant integrations.

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Estimated $0.80–$1.60/hr while serving · Long-running endpoint — starts in 3–6 min

What inputs you need

  • Model: Qwen/Qwen2.5-Coder-32B-Instruct (or pinned variant)
  • Max-cost budget
  • Optional: context-length override for large repos/files

What Badgr returns

  • OpenAI-compatible endpoint URL + API key
  • Health-check status
  • Usage receipt on teardown

Recommended GPU routes

H100 80GBA100 80GBL40S 48GB

Estimated cost: $0.80–$1.60/hr while serving · Estimated runtime: Long-running endpoint — starts in 3–6 min

Example command

badgr serve Qwen/Qwen2.5-Coder-32B-Instruct \
  --gpu H100 \
  --max-cost 15

Common setup failures Badgr avoids

Context length errors on long file/repo prompts — route to a higher-VRAM GPU (A100 80GB or H100) and confirm the model's max context before large-context calls.

Endpoint fails health check on cold start — startup timeout accounts for larger coder-model weight sizes.

Ready to run this?

Launch from the dashboard, CLI, or Compute API. Max-cost protection included.

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