Inference provider · Inference gateway
Prime Intellect Inference
Verified Sep 2026
Quick answer: Open/custom model inference on Prime Intellect training-and-eval stack — OpenAI-compatible pinference API, `prime env eval`, and dedicated/LoRA/serverless deploys when you want one platform from lab to production inference.
Best for
Open/custom model inference on Prime Intellect training-and-eval stack — OpenAI-compatible pinference API, `prime env eval`, and dedicated/LoRA/serverless deploys when you want one platform from lab to production inference.
Skip if
You want the widest multi-provider aggregator (OpenRouter), published per-model pricing today, or the Prime Agent CLI harness (Agents shelf) rather than a BYOK inference key.
Who it fits
- Open/custom model inference on Prime Intellect training-and-eval stack — OpenAI-compatible pinference API, `prime env eval`, and dedicated/LoRA/serverless deploys when you want one platform from lab to production inference.
- Builders who start in the browser without a local IDE setup
- Terminal-first engineers who live in the shell and git
Pros
OpenAI-compatible inference API at `https://api.pinference.ai/api/v1` on the same Prime Intellect stack that trains models — routes to various providers for open and custom models; dedicated deploys, LoRA adapters, and serverless endpoints for your checkpoints; evals-first workflow (`prime inference models`, `prime env eval`); token billing from Prime balance; team accounts via `X-Prime-Team-ID`.
Cons
Per-model pricing not fully published in docs ("more details on pricing soon"); eval/RL-lab shaped vs a general OpenRouter-style hobby gateway; not the Prime Agent CLI harness (separate Agents-shelf card at `/tools/prime-agent`); not hands-on verified here.
Facts
- Locality:
- Cloud-native
- Surfaces:
- Web, CLI
- Maturity:
- Experimental
- Open source:
- Source available
- Verified:
- Sep 2026
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