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gpt-oss-20b (vLLM)

Published, not hardware-testedvllmmxfp4LLM inference

gpt-oss-20b on vLLM for high-throughput batched serving.

Needs 22 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
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Runs
0
Min VRAM
24 GB
Backend
CUDA · NVIDIA GPUs
Version
vllm-gpt-oss-20b-v1.0.0
Image digest
4895d4c39da6…
Health check
SSH probe on the leased endpoint

OpenAI-compatible API on the leased HTTP endpoint (per-job API key from the rental's access panel). Weights (13.8 GB safetensors) are warmed into the host cache and mounted read-only. vLLM's MXFP4 path needs a recent GPU; consumer Ampere/Ada support is UNVERIFIED. Thin AmpleRun wrapper (templates/images/workspace, variant serve-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). Weights: Apache-2.0 (openai/gpt-oss-20b) (https://huggingface.co/openai/gpt-oss-20b). 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 #reasoning #openai-api #vllm

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