Lifeboat
Run 2–6x more agents on the GPU you already have
22 followers
Run 2–6x more agents on the GPU you already have
22 followers
Your agents keep multiplying, but your GPU budget doesn't. Lifeboat fits 2–6x more concurrent agents on the same card at full model precision — no quantization, no quality loss. Confidential compute is built in (TEE attestation, weights encrypted in use), so sensitive data never leaves your perimeter. One engine from a DGX Spark on your desk to B300s in the rack. OpenAI-compatible, native ROCm, free dev license. Download it today: https://iterate.ai/lifeboat
Free
Launch Team
ClarifyThe autonomous CRM that helps you sell more
Promoted
I have been inferencing Qwen3.8 27B on an NVIDIA L40S with 48 GB of VRAM. There is a RAG pipeline which needs to rate relevance of 60 chunks (each 1024 tokens or less) against user's queries. Parallelizing this relevance rating process would be great as it would greatly reduce the response time of the RAG pipeline. However, currently I am struggling to to even pack 3-4 reqs to the model at a time without some hanging / degradation on Ollama inference. Can LifeBoat help in this context?
10,000 downloads in the first week. Lifeboat runs inference on hardware you already own — OpenAI-compatible API, 2–6x higher concurrency than SGLang on the same GPU, data stays on your network. Fast, cheaper than per-token cloud, and built for real agent load.
Got to work on this one and I'm so glad it's finally out there! 🙌
If you self-host, grab the free dev license and let us know what you see. Would genuinely love the feedback.
Lifeboat is honestly one of the most exciting things we've developed at Iterate.ai. I can't wait to see where it goes from here.
We just launched Lifeboat—the first inference engine built for how agents actually work, not chatbots. It doubles your GPU capacity without touching model quality. Would love to hear what you think!