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.
Not given
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
Constant-state attention: models serve any context length from the same memory per request
HCGM: models run from disk storage instead of memory
M-Rail: context processed by a model can be reused instantly in future requests
CPUDA/sGPU: run unmodified CUDA programs on CPUs with bit-identical results
Organ grafting: transfer capabilities between models without training
Personal instruction set (ISA) compiled on device from phone signals
Population ISA: compile laws from many people without personal records
Digital twins of customers, fleets, cities or markets
Results identical across all machines and architectures
Computation cost follows novelty not data size
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
Constant memory cost regardless of context length or data size
Exact reuse: every computed result is kept and reused instantly
Portable execution with bit-identical results across all hardware
Models run from storage without retraining or fitting in memory
Privacy-preserving: raw data never leaves the device