Compute on-demand: H200 starting at $0.47/HR to $1.99/HR, B300 at $4.99/HR, B200 at $3.49/hr, H100 at $2.43/HR (Spot $0.94/HR). Reserved clusters available with quotes from 50+ datacenters.
Free: 1M context tokens (one-time). Pro: $15/month for 100M tokens/month, $0.18 per extra 1M tokens. Scale: $49/month for 350M tokens/month, $0.15 per extra 1M tokens. 30% off Pro or Scale for the first year for early access teams.
Key features
2,500+ RL environments on the Hub
100+ open-source model evaluations
Managed training workflows with full visibility
GLM-5.3 hosted inference
OpenAI-compatible API
SLURM and Kubernetes orchestration
Infiniband networking for distributed training
Grafana monitoring dashboards
Secure code sandboxes for RL
Removes duplicate context and off-topic results
Works with any LLM provider
API and SDK integrations
Quality guard checks if kept context is sufficient
Local cleanup of tool output and JSON fields
Fallback to original context on service failure
Per-agent budgets and token limits
Savings report showing cost avoided
What makes it different
Integrated stack combining training, inference, compute and evaluations in one platform
Backed by leading investors including NVIDIA, Founders Fund, and AI researchers
Large-scale open-source community with 2,500+ environments and models
Applied research team providing hands-on support for training
Competitive pricing with spot market and reserved cluster options
Reduces input tokens to LLMs by 56–71% on average
Optimizes in milliseconds without slowing requests