Prime Intellect
by Prime Intellect
The open superintelligence stack — own your intelligence with custom compute, RL training, and inference in one platform.
Prime Intellect is a full-stack AI infrastructure platform that lets enterprises train, fine-tune, and serve their own agentic models without depending on frontier labs. It combines an on-demand GPU marketplace, a reinforcement-learning training framework, 2,500+ RL environments, and OpenAI-compatible inference for AI teams that want to avoid vendor lock-in.
Prime Intellect is an end-to-end AI infrastructure platform — billed as 'The Open Superintelligence Stack' — that gives enterprises the compute, training tools, and serving infrastructure to build and continuously improve their own AI agents and models rather than relying on closed frontier labs. The platform spans four layers: a compute marketplace offering on-demand GPUs (1–256 units, spot and reserved) across 50+ cloud providers with SLURM/Kubernetes orchestration and InfiniBand networking; a training 'Lab' with hosted large-scale runs and 2,500+ reinforcement-learning environments that iteratively reward successful task completion and penalize errors; dedicated inference with serverless, OpenAI-compatible APIs and pay-per-token LoRA adapter serving; and an open Environment Hub built on its open-source Verifiers and Prime-RL libraries. Founded in 2024 and led by CEO Vincent Weisser, the company raised a $130M Series A in July 2026 at a $1 billion valuation led by Radical Ventures with Nvidia Ventures, Intel Capital, and Dell Technologies Capital, and reports a $100M annualized revenue run rate with customers including Ramp, Zapier, and Character AI.
At a Glance
- Category
- Infrastructure & Cloud
- Pricing
- Usage-based
- Target Market
- CTOs, AI/ML Engineers, Data Scientists, Enterprise Developers
- Founded
- 2024
Key Features
- ✓Compute marketplace
On-demand GPUs from 1 to 256 units with spot and reserved pricing across 50+ providers, plus SLURM/Kubernetes orchestration and InfiniBand networking.
- ✓RL environments hub
2,500+ community and hosted reinforcement-learning environments for training agents on specific business tasks.
- ✓Managed training (Lab)
Hosted large-scale, agentic-workflow-optimized model training with full visibility and applied-research support.
- ✓OpenAI-compatible inference
Serverless production serving with custom routing, latency optimization, and pay-per-token LoRA adapter hosting.
- ✓Open-source tooling
Verifiers (modular RL environment components) and Prime-RL (asynchronous RL framework) released as open source.
Capabilities
Use Cases
- •Build a proprietary agent without frontier-lab lock-in
Enterprises train and own domain-specific agentic models on their own data using Prime Intellect's integrated stack.
- •Reinforcement-learning fine-tuning
Teams refine models against reward-based RL environments to improve reliability on specific workflows.
- •Cost-optimized GPU access
AI teams source spot or reserved GPU clusters across 50+ providers to control training and inference costs.
Ideal For
Best For
- ✓Training and fine-tuning custom agentic models with reinforcement learning
- ✓On-demand and reserved GPU compute across multiple clouds
- ✓Serving fine-tuned LoRA adapters via OpenAI-compatible APIs
Integrations
Market Analysis
Pros
- ✓End-to-end stack removes need to stitch together separate compute, training, and inference vendors
- ✓Strong RL environment library for task-specific agent training
- ✓Backed by strategic chip/hardware investors (Nvidia, Intel, Dell)
Cons
- ✗Building and owning models requires more ML expertise than calling a frontier API
- ✗Young company (founded 2024) still scaling enterprise support
Pricing
Compute (usage-based)
Usage-based
- ✓On-demand GPUs (e.g. H200 ~$0.47–$1.99/hr, B300 ~$4.99/hr)
- ✓Spot and reserved clusters
- ✓Pay-per-token LoRA inference
Reserved clusters
Contact for pricing
- ✓Reserved GPU capacity via quote
- ✓Managed training and inference
Compute is billed per GPU-hour with published spot rates; reserved clusters are quoted.
Sources
This page was written from 2 sources, 1 on domains other than primeintellect.ai.
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