Private AI inference and confidential GPU computing infrastructure
Python SDK for LoRA fine-tuning with supervised fine-tuning and reinforcement learning
Stage
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Founded
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Based in
US
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Pricing model
Paid
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Pricing
Confidential Inference: DeepSeek V4.1 Flash $0.30 input and $1.20 output per 1M tokens; Kimi K3 $3.00 input and $15.00 output per 1M tokens; GLM 5.3 $1.40 input and $4.40 output per 1M tokens; Qwen3.8 27B $0.30 input and $1.80 output per 1M tokens. Confidential VMs: B300 at $7.50 per GPU-hour, B200
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Key features
OpenAI-compatible endpoint for private LLM inference
Hardware-encrypted VMs on Intel TDX, AMD SEV-SNP and NVIDIA GPUs
Client attestation verification before sending requests
Support for multiple open-weight models including DeepSeek, Kimi, GLM, Qwen
Confidential Kubernetes for data center scale deployments
Confidential training and fine-tuning on licensed stack
Root access over SSH to confidential VMs
Encrypted GPU communications with NVLink encryption on B200 and B300
Confidential agents runtime support
Prompt caching with cached input billing
forward_backward() operation for computing loss and accumulating gradients
optim_step() for updating the adapter
sample() for generating from current or saved policy
save_state() to save and resume training state
Tinker API compatibility
Separate trainer and sampler resources
Synchronous and asynchronous RL patterns
Frozen base model weights with LoRA adapter updates
Support for open models from Qwen, Google, DeepSeek, Moonshot AI, NVIDIA, and Z.ai
What makes it different
Prompts and model weights verified by clients with cryptographic attestation before any data is sent
Operator-blind inference: data remains unreadable to the company and hosting provider
Flexible deployment: choice of hosted cloud, rented VMs, or licensed stack on own infrastructure
Open-weight models only, no closed-source frontier models
Full cryptographic verification stack including open-source tools
Managed training and sampling infrastructure, no setup required
Tinker-compatible API for easy migration
Ready-made SFT and RL recipes through Loops cookbook