Paste your workload
Badgr checks your workload for free before any GPU starts.
No GPU starts. No charge.
Badgr Preflight
Paste a repo, model, command, GitHub issue, Docker image, error log, or conversation. Badgr inspects it, tells you exactly what’s missing, and checks the result — free, with no GPU involved. A capped Smoke Test on a real GPU is an optional next step, on your call.
Badgr checks your workload for free before any GPU starts.
No GPU starts. No charge.
Give Badgr your mess - a command, repo, model, Docker image, GitHub issue, or conversation - and it tells you exactly how to run it.
Skip the hour of reading docs, guessing entrypoints, and trial-and-error. Badgr turns that into minutes.
Badgr smoke-checks the setup for free first, catching dumb setup failures before you fund the expensive part.
Paste it, get a runnable command, verify on GPU only if you want proof.
A repo, model, command, GitHub issue, Docker image, error log, or conversation. One box - Badgr figures out what it is.
AI and static inspection produce a runnable command, flag what’s still missing, and smoke-check it — free, no GPU involved.
Want proof it actually runs? Approve a capped GPU test with a hard cost limit. Nothing runs without that approval.
One box. Badgr detects which of these it is - you don’t have to say.
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.
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.
Badgr shows one maximum spend in USD (e.g. $5.00) before you approve - never an estimate mixed with the cap, and never a different currency. You’re only charged for actual runtime - unused reservation is released immediately.
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.
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.