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 # or: pip install prime
prime login # browser auth; or: prime config set-api-key
prime config view # verify configuration
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 # discover pages
curl -s https://docs.primeintellect.ai/sandboxes/overview.md # fetch a page as markdown
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
# Environments Hub
prime env list --search "math" # discover environments
prime env info owner/name # inspect one
prime env install owner/name # install locally
prime env init my-env --v1 # scaffold a new environment
prime env push # publish to the Hub
# Evaluations
prime eval run my-env -m openai/gpt-4.1-mini -n 5 # local smoke eval
prime eval run owner/env --hosted --follow # hosted eval with logs
# Training
prime lab setup # set up a Lab workspace (Hosted Training)
prime train models # models, capacity, pricing
prime train init && prime train rl.toml # configure + launch a run
# Sandboxes
prime sandbox create python:3.11-slim --timeout-minutes 120
prime sandbox run <sandbox-id> "python --version"
prime sandbox delete <sandbox-id>
# Inference
prime inference models # list available models
# Compute
prime availability list # GPU availability + pricing
prime pods create # provision a pod
prime pods ssh <pod-id> # SSH in (needs: prime config set-ssh-key-path)
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.
1---2name: prime-intellect3description: 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.4---56# Prime Intellect78Prime 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.)910## Product Map1112| Product | What it is | Details |13|---|---|---|14| verifiers | Python library for building LLM environments and evaluations | [environments.md](references/environments.md) |15| Environments Hub | Platform library of community RL environments (`prime env`) | [environments.md](references/environments.md) |16| Hosted Evaluations | Run evals on Prime-managed infra (`prime eval run --hosted`) | [environments.md](references/environments.md) |17| Hosted Training | Post-train models against environments (`prime train`, Lab) | [environments.md](references/environments.md) |18| prime-rl | Large-scale async RL framework for self-managed training | [environments.md](references/environments.md) |19| Sandboxes | Secure disposable Docker environments for AI-generated code | [sandboxes.md](references/sandboxes.md) |20| Tunnels | Public HTTPS URLs for local/sandboxed services | [sandboxes.md](references/sandboxes.md) |21| Inference | OpenAI-compatible API for frontier models | [inference.md](references/inference.md) |22| Compute | Rent single GPU pods or multi-node clusters | [compute.md](references/compute.md) |23| Storage | Persistent disks shared between instances | [compute.md](references/compute.md) |2425## Prime CLI Setup2627Default to the `prime` CLI for all Prime Intellect operations. If it is not installed:2829```bash30uv tool install prime # or: pip install prime31prime login # browser auth; or: prime config set-api-key32prime config view # verify configuration33```3435The same package provides the Python SDKs (e.g. `prime_sandboxes`, `prime_tunnel`). Source: https://github.com/PrimeIntellect-ai/prime3637## Live Documentation3839Authoritative, 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:4041```bash42curl -s https://docs.primeintellect.ai/llms.txt # discover pages43curl -s https://docs.primeintellect.ai/sandboxes/overview.md # fetch a page as markdown44```4546The 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.4748## Command Quick Reference4950```bash51# Environments Hub52prime env list --search "math" # discover environments53prime env info owner/name # inspect one54prime env install owner/name # install locally55prime env init my-env --v1 # scaffold a new environment56prime env push # publish to the Hub5758# Evaluations59prime eval run my-env -m openai/gpt-4.1-mini -n 5 # local smoke eval60prime eval run owner/env --hosted --follow # hosted eval with logs6162# Training63prime lab setup # set up a Lab workspace (Hosted Training)64prime train models # models, capacity, pricing65prime train init && prime train rl.toml # configure + launch a run6667# Sandboxes68prime sandbox create python:3.11-slim --timeout-minutes 12069prime sandbox run <sandbox-id> "python --version"70prime sandbox delete <sandbox-id>7172# Inference73prime inference models # list available models7475# Compute76prime availability list # GPU availability + pricing77prime pods create # provision a pod78prime pods ssh <pod-id> # SSH in (needs: prime config set-ssh-key-path)79```8081## Working Conventions8283- Prefer ecosystem-native paths (`prime env init`, `prime eval run`, `prime lab setup`) over custom scaffolding.84- Smoke-test small (`-n 5`) before scaling evals or training; keep default result uploads unless the user explicitly opts out.85- 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).86- Hosted Training launches from a CPU machine; self-managed `prime-rl` requires local GPU access and is a power-user path.87- The dashboard at https://app.primeintellect.ai covers API keys, billing, teams, and anything the CLI does not.
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