Resources // AI Infrastructure
Beam (Beam Cloud)
Offer $30/mo of serverless-GPU credit
Suits for Non-VC-backedCreatorsResearchersOpen-source
Updated Jun 2026
The offer
- $30 in compute credits every month, refreshed monthly, on the free Developer tier ($0/mo)
- Serverless GPUs billed by the second: RTX 4090 ~$0.000192/s (~$0.69/hr), A10G ~$0.000292/s (~$1.05/hr)
- On-demand GPUs: A100 80GB from ~$1.30/hr, H100 from ~$1.74/hr, H200 from ~$1.99/hr
- No charge for cold-start / container spin-up; storage volumes included
- Developer tier: 5 GPU containers + 30 CPU containers of concurrency, unlimited apps, 1 seat (Team tier $89/mo raises limits)
Who qualifies
- Open self-serve signup at the Beam platform, no application
- A card is typically required for usage beyond the monthly credit
- The free Developer tier caps you at 1 seat and 5 concurrent GPU containers
Community Insights
Beam is a serverless-GPU platform in the same space as Modal, and its pitch is fast cold starts, a caching layer for model files, and pay-only-for-inference billing. Independent signal is thin (most of its Hacker News presence is founder posts), but the one production account that switched from Replicate praised consistently small cold starts and easy model/LoRA hot-swapping via cached volumes. The $30 monthly credit makes it cheap to try without committing.
Best Practices (from community tips)
- Use serverless / per-second billing for spiky inference. The $30 credit goes furthest there.
- Lean on the volume / caching layer to avoid re-downloading weights when swapping models or LoRAs.
- Keep apps spinning down by default; only keep-warm latency-sensitive endpoints.
- Import existing Docker images instead of rebuilding to save iteration time.
- Watch the 5-GPU-container cap on the free tier before promising production SLAs.
- Consider the open-source engine (beta9) if data must stay in your own VPC.