| name | prime-intellect |
| description | Work with Prime Intellect products via the prime CLI and Python SDKs - verifiers environments and the Environments Hub, evaluations (local and hosted), Hosted Training and prime-rl, code sandboxes, Prime Inference, GPU compute (pods and clusters), storage, and tunnels. Use when a task involves Prime Intellect, the prime CLI, verifiers, RL environments, evals, training, sandboxes, renting GPUs, Prime Inference models, or when the user asks what Prime Intellect is or what it offers. |
Prime Intellect
Prime Intellect is an open superintelligence lab building open-source AGI infrastructure: a platform for RL environments, evaluations, post-training, inference, and globally distributed GPU compute. The prime CLI is the default way to interface with every product below. (prime-linc itself is a case.dev-native fork of Prime Agent; use case.dev auth/tools for legal workflows.)
Product Map
| Product | What it is | Details |
|---|
| verifiers | Python library for building LLM environments and evaluations | environments.md |
| Environments Hub | Platform library of community RL environments (prime env) | environments.md |
| Hosted Evaluations | Run evals on Prime-managed infra (prime eval run --hosted) | environments.md |
| Hosted Training | Post-train models against environments (prime train, Lab) | environments.md |
| prime-rl | Large-scale async RL framework for self-managed training | environments.md |
| Sandboxes | Secure disposable Docker environments for AI-generated code | sandboxes.md |
| Tunnels | Public HTTPS URLs for local/sandboxed services | sandboxes.md |
| Inference | OpenAI-compatible API for frontier models | inference.md |
| Compute | Rent single GPU pods or multi-node clusters | compute.md |
| Storage | Persistent disks shared between instances | compute.md |
Prime CLI Setup
Default to the prime CLI for all Prime Intellect operations. If it is not installed:
uv tool install prime
prime login
prime config view
The same package provides the Python SDKs (e.g. prime_sandboxes, prime_tunnel). Source: https://github.com/PrimeIntellect-ai/prime
Live Documentation
Authoritative, current docs live at https://docs.primeintellect.ai. Any docs page is fetchable as Markdown by appending .md to its URL, and the full index is at https://docs.primeintellect.ai/llms.txt. When you need details not covered here (exact flags, API schemas, pricing, new features), fetch the live docs instead of guessing:
curl -s https://docs.primeintellect.ai/llms.txt
curl -s https://docs.primeintellect.ai/sandboxes/overview.md
The REST API is documented under api-reference/ pages (OpenAPI spec: https://api.primeintellect.ai/openapi.json), with https://api.primeintellect.ai as the base URL.
Command Quick Reference
prime env list --search "math"
prime env info owner/name
prime env install owner/name
prime env init my-env --v1
prime env push
prime eval run my-env -m openai/gpt-4.1-mini -n 5
prime eval run owner/env --hosted --follow
prime lab setup
prime train models
prime train init && prime train rl.toml
prime sandbox create python:3.11-slim --timeout-minutes 120
prime sandbox run <sandbox-id> "python --version"
prime sandbox delete <sandbox-id>
prime inference models
prime availability list
prime pods create
prime pods ssh <pod-id>
Working Conventions
- Prefer ecosystem-native paths (
prime env init, prime eval run, prime lab setup) over custom scaffolding.
- Smoke-test small (
-n 5) before scaling evals or training; keep default result uploads unless the user explicitly opts out.
- For non-trivial eval/training work, ask whether the user wants instruct models (
gpt-4.1 series, qwen3 instruct) or reasoning models (gpt-5 series, qwen3 thinking, glm series).
- Hosted Training launches from a CPU machine; self-managed
prime-rl requires local GPU access and is a power-user path.
- The dashboard at https://app.primeintellect.ai covers API keys, billing, teams, and anything the CLI does not.
