| What it does | The API between AI agents and silicon
| Python SDK for LoRA fine-tuning with supervised fine-tuning and reinforcement learning
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| Stage | Not given
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| Founded | 2023
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| Based in | DE
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| Pricing model | Freemium
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| Pricing | Free tier: 1,000 credits per day, resets every 24 hours. Pay-as-you-do: €10 per 1,000 credits. Enterprise: Custom pricing with volume commit, on-prem, and SLAs.
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| Key features | - Compile firmware against production toolchains remotely without installation
- Execute firmware on virtual chip instances with verdict, trace, and register state
- Unit and integration testing on virtual hardware with coverage reports
- Inject synthetic sensor data into running firmware
- Query collective embedded corpus for chip-specific solutions
- Support for Rust, C, and multiple RTOS frameworks
| - 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
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| What makes it different | - Virtual instances of actual target chips, not generic CPU emulation, with same binary, peripherals, and interrupt timing as physical boards
- Shared corpus that deepens with every call, allowing agents to inherit knowledge from previous runs
- Eliminates need for physical hardware for testing, porting, and debugging
- Single MCP endpoint exposes cross-compilation, peripheral simulation, sensor IO, and chip-specific plumbing
- Access to licensed toolchains on demand without local installation
| - Managed training and sampling infrastructure, no setup required
- Tinker-compatible API for easy migration
- Ready-made SFT and RL recipes through Loops cookbook
- Support for vision-language models
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 28 ▼ −1 (down) since last check | 77 ● no change since last check |
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| Trust Flow (Majestic) | 5 | 13 |
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| Citation Flow (Majestic) | 27 | 43 |
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| Referring domains (Majestic) | 117 | 550 |
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Chiplab
Loops