Market insights

Free Cloud GPU Credits in 2025: 10 Programs Worth $250k+

September 16, 2025
6 mins read

Why credits still matter

GPU prices have fallen, but A100 80 GB time is still money. The fastest way to extend runway is to chain free‑credit programs, starting with quick wins (no funding needed) and graduating to hyperscaler bundles when you raise. Below are the ten richest offers live today. All amounts are “up to” and subject to each provider’s terms.

Program & one‑click link Headline credit Key eligibility GPU angle
Thunder Compute Credit Match – Sign up 100 % match on first $50 spend + $20 for students + 3 % lifetime referral Anyone A100 80 GB at $0.78/hr billed per‑second, snapshots, live spec changes
Google for Startups Cloud (AI Tier) – Google AI credits (Google Cloud) $350 k VC‑backed AI startups up to Series A Use credits on H100, A3 Ultra, TPU v5e
AWS Activate Portfolio – AWS Activate (Amazon Web Services, Inc.) $100 k (GenAI path up to $300 k) Accelerator/VC intro & ≤Series B Covers P5/H100 and G6e/RTX 4090
Microsoft for Startups Founders Hub – Founders Hub (Microsoft for Startups) $150 k Product live + verified traction (no funding required) ND A100 at $3.40/hr plus Azure ML
IBM Startup with IBM – IBM Cloud credits (IBM Cloud) $120 k <5 yrs old, less than $1M rev Access to NVIDIA L40S, V100, A100 on IBM Cloud
DigitalOcean Hatch (AI Upgrade) – Hatch details (DigitalOcean) $100 k + 3 mo free 8×H100 droplet Pre‑seed–Series A; incubator or direct Simpler UI than hyperscalers, K8s GPU add‑on
Alibaba Cloud Startup Catalyst – Catalyst (alibabacloud.com) $120 k lifetime (regional caps) APAC‑focused startups Cheapest H100s in Singapore region
OVHcloud Startup Program – OVHcloud Scale level (OVHcloud) €100 k (~$109 k) EU tech scaleups EU‑sovereign A100 & L40S at low latency
Scaleway Startup Program – Scaleway (Scaleway) €36 k (~$39 k) EU early‑stage H100 & Mac Mini GPU‑ready regions
Oracle for Startups – Oracle credits (OneClick IT Consultancy) $10 k–$50 k Global B2B, no equity asked OCI bare‑metal A100 with RDMA NVLink fabric
Quick stacking game‑plan
  1. Start day‑zero – activate Thunder match and student credit to validate on cheap A100s.
  2. Layer indie perks – grab DigitalOcean Hatch for extra H100 test time.
  3. Scale with hyperscalers – once funded, pull in Google ($350 k) + AWS ($100 k) to cover peak training bursts.
  4. Stay portable – snapshot to S3‑compatible storage, then restore on Thunder when credits expire.
Pro tip: mixing credits typically lets a 5‑person ML team run continuous A100/H100 training for 9‑12 months with <5 % out‑of‑pocket spend.

Your GPU,
one click away.

Spin up a dedicated GPU in seconds. Develop in VS Code, keep data safe, swap hardware anytime.

Get started