Inferix vs Lambda
Lambda is a raw GPU cloud — great for training, but it's winding down serverless token inference, has no model hub, and no attestation. Inferix keeps the GPU rental and adds OpenAI-compatible endpoints, a full hub, hardware attestation + Proof-of-Render, per-second billing, and self-host.
| Capability | Inferix | Lambda |
|---|---|---|
| Rent GPUs | Rent verified GPUs by the second, or host your own | Instances + 1-Click Clusters |
| OpenAI-compatible endpoints | OpenAI-compatible — swap the base URL, your SDK works unchanged | Winding down serverless inference |
| Hardware-attested GPUs | Hardware-attested GPUs; jobs verified before they run | |
| Per-job Proof-of-Render | Per-job Proof-of-Render, geo-attested to the region you approve | |
| Model / dataset / Spaces hub | Models, datasets, Spaces, collections, leaderboards, follow graph | |
| Semantic search across models | Real semantic search across the hub | |
| Fine-tune → one-click deploy | Fine-tune on rented GPUs, one-click deploy to an endpoint | Infra for training, no hub |
| Self-hostable / sovereign | Self-hostable / sovereign — data residency + geo-attestation | |
| Per-second billing | Billed by the second | Per-hour instances |
| Scale-to-zero serverless | Scale-to-zero serverless endpoints |
Based on each platform's public site and docs as of October 2026; capabilities evolve — check live pricing and docs before deciding. full partial not offered
Where Lambda is strong
Lambda offers strong raw GPU instances and self-serve 1-Click Clusters over InfiniBand for large training runs.
Choose Lambda if your main need is large multi-node training on dedicated clusters over InfiniBand.
Where Inferix wins
Choose Inferix if you want GPU rental plus endpoints, a hub, per-second billing, and attestation in one platform.
Try the platform Lambda can't be
A verified GPU marketplace, OpenAI-compatible endpoints, and a full model hub — in one account, billed by the second.