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vLLM workspace

Published, not hardware-testedociLLM inference

SSH workspace with vLLM installed: serve any model you choose with `vllm serve`.

Needs 15 GiB VRAM · CUDA on NVIDIA

No GPU big enough is free right now.

New machines appear as hosts connect them.

No speed benchmarks yet, so we match on price.

Template details
Rating
No ratings yet
Runs
0
Min VRAM
16 GB
Backend
CUDA · NVIDIA GPUs
Version
vllm-workspace-v1.0.0
Image digest
d72482c035df…
Health check
SSH probe on the leased endpoint

SSH as `tenant` with your key; tools are on PATH. Models download into /work at your request (public egress is allowed; private networks are blocked). Reach a server on port 8000 with `ssh -L 8000:127.0.0.1:8000`. Thin AmpleRun wrapper (templates/images/workspace, variant ws-vllm) over vllm/vllm-openai:v0.30.0-cu129@sha256:a67f8f186d4567612ac37a55bd82295006002b18858eb12a8af2f05f86c2ae3f (digest verified 2026-09-26); NOT BUILT, so image_digest is a placeholder that can be neither published nor rented. Licence: Apache-2.0 (https://github.com/vllm-project/vllm/blob/main/LICENSE). Needs an NVIDIA driver that supports CUDA 12.9 or newer. Status: not hardware-tested.

We match GPUs on their measured runtime and dedicated VRAM. A hardware report doesn't qualify another vendor's backend.

#llm #vllm #workspace

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Deploy vLLM workspace · AmpleRun