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gpt-oss-120b on RBLN NPU

Install the RBLN Driver on the host. An RBLN Portal account is required to install the RBLN Compiler (rebel-compiler). See the installation matrix for compatible package versions.

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$ pip install \
  --extra-index-url https://pypi.rbln.ai/simple \
  rebel-compiler==0.12.0

The KV offload (LMCache) commands need the kv_connectors extra, which installs lmcache-rbln and nixl-rbln. Without it those servers fail at startup.

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$ pip install \
  --extra-index-url https://pypi.rbln.ai/simple \
  --extra-index-url https://wheels.vllm.ai/0.30.0/cpu \
  --extra-index-url https://download.pytorch.org/whl/cpu \
  "vllm-rbln[kv_connectors]==0.12.0"

Suffix decoding (the Suffix option under Speculative Decoding) needs arctic-inference, which vllm-rbln does not install by default. Without it that server fails at startup with an ImportError.

$ pip install arctic-inference==0.1.1
Guide — overview and configuration

Overview

openai/gpt-oss-120b is a Mixture-of-Experts, decoder-only model. On RBLN NPUs, the RBLN vLLM plugin compiles it on first run for a fixed batch size, sequence length, and NPU count, then serves it over vLLM's OpenAI-compatible API.

Configuration

Verified on RBLN-CR13. Every strategy in the recipe above is aggregated: one server takes every request on one device.

Every command runs on the vllm model implementation, selected with --model-impl vllm.

Recipes for other model sizes:

gpt-oss-20b

See the Configuration Guide for all engine arguments.

Notes and limitations

  • The batch size, sequence length, and NPU count are fixed at compilation; changing any of these settings triggers recompilation at the next startup.
  • The latency strategies serve with --max-num-seqs 1 and the throughput strategies with a larger value. Changing it recompiles the model.