Badgr Run Issue

Debug GPU issues faster.
Paste it. Badgr verifies it.

Paste a Discord thread, Slack message, GitHub issue, Docker image, or error log. Badgr detects the workload, redacts secrets, and finds the cheapest safe GPU to verify it.

Free diagnosisSecrets redacted before any AINo GPU without your approvalHard cost cap - no surprises
Submit your issue

How it works

Five steps from messy conversation to a verified GPU command - no manual debugging.

Step 1

Paste your issue

Paste a Discord thread, Slack message, support ticket, error log, GitHub issue URL, Docker image, or repository URL.

Step 2

Badgr detects it

AI extracts the workload, image, model, launch command, errors, and any details still needed.

Step 3

Static inspection

Known configurations, multi-GPU flags, and large-model download requirements are checked before a test is proposed.

Step 4

Choose how to proceed

Review the proposed test, copy the exact command to run yourself, or continue to verification.

Step 5

Get your evidence

A private result page shows every execution stage, the verified exact command, actual cost, and teardown confirmation.

What you can submit

Any format your team uses to share GPU issues - Badgr handles the extraction.

Conversation threads

Discord, Slack, email, or support tickets - paste the whole thread, Badgr extracts the signal.

GitHub issue URL

Badgr safely fetches the issue title, body, and comments via the GitHub API.

Docker image

Submit an image name. Badgr uses known image patterns and asks you to confirm the detected workload details.

Repository URL

Badgr reads Dockerfiles, launch scripts, and configs via the GitHub API file tree.

ComfyUI workflow

Paste a workflow JSON and Badgr extracts nodes, models, and missing custom nodes.

Error logs

CUDA OOM messages, stack traces, startup failures - any error log becomes a structured reproduction plan.

Submit your issue

Diagnosis is free and secrets are redacted before AI processing. A GPU runs only after you approve the displayed hard cost cap.

Common questions

Is the diagnosis really free?

Yes - detection, secret redaction, AI extraction, static inspection, and template matching are all free. You only pay if you choose to run a GPU test, and the maximum charge is shown before you approve.

What happens to my secrets?

Badgr runs a pattern-matching redactor over your pasted text before sending anything to an external AI model. API keys, tokens, and passwords are replaced with [REDACTED]. Only the variable names are stored - never the values.

What does a capped GPU test cost?

The price depends on the workload and GPU selected. Badgr shows an estimated range and a hard maximum (e.g. AUD $0.80–$2.40) before you approve. You’re only charged for actual runtime - unused reservation is released immediately.

What is sponsorship?

For simple workloads costing ≤ $2 USD with no multi-GPU requirement and no large model download, you can request Badgr to sponsor the GPU test. A human reviews and reaches out - no GPU runs automatically.

Can I just get the command and run it myself?

Yes. On the approve screen, click “Run it yourself” to reveal the exact Badgr CLI command, recommended GPU, VRAM, and runtime cap. No payment or account needed for that.

What workloads does Badgr support?

vLLM serving, ComfyUI image generation, PyTorch training (torchrun / Deepspeed / Axolotl / TRL), lm-evaluation-harness, and generic Docker containers. More are added as verified templates accumulate.