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OpenAI
openai/gpt-oss-safeguard-20bCatalogue: Indexed in the reference catalogue; nothing on this deployment answers as this model yet.
Published by the vendor; the platform bills at the target's declared price.
OpenAI openai/gpt-oss-safeguard-20b
gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model offers lower latency for safety tasks like content classification, LLM filtering, and trust...
gpt-oss-safeguard-20b earns a request when it needs step-by-step reasoning, tool calls, running on your own hardware; a short, general request would go to Nemotron 3.5 Super VL (free) instead - free per million input tokens against $0.07 here; and the hardest requests, where the quality floor rules it out, to Claude Opus 5.5 (batch). Your rules decide the floor; the trace shows the comparison for every request.
Lower input price and an intelligence index within 5 points (this model has no published index).
Nothing on this deployment answers as this model yet. Connect your own provider under Model providers, or add a target to your catalogue - the router picks it up without retraining.
# targets.yaml - declare a target that runs gpt-oss-safeguard-20b
targets:
- id: gpt-oss-safeguard-20b
kind: llm
name: gpt-oss-safeguard-20b
metadata:
model: openai/gpt-oss-safeguard-20b # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: true
context_window: 131072
cost:
usd_per_1k_tokens: 0.000188Input list price per million tokens; gpt-oss-safeguard-20b is the 3rd cheapest of 13 listed.
Photo: RDNE Stock project
Cached input reads $0.04 per 1M · weights on Hugging Face as openai/gpt-oss-safeguard-20b
A higher intelligence index, best first, with the price it comes at.
Other models by the same vendor in the catalogue.
The catalogue prints input and output prices and what three typical monthly workloads cost on each.