{"id":"openai-gpt-oss","name":"gpt-oss","af_score":40.0,"security_score":18.8,"reliability_score":26.2,"what_it_does":"gpt-oss is a Python repository providing reference inference implementations and tool/client examples for OpenAI’s open-weight gpt-oss models (gpt-oss-20b and gpt-oss-120b). It includes local inference via PyTorch, optimized (reference) Triton, and Apple Silicon Metal (reference), plus “harmony” response-format tooling and reference implementations of model tools (browser and python) and a sample Responses-API-compatible server.","best_when":"You want local, open-weight model inference with the accompanying harmony format and reference tool implementations, and you can provide the necessary compute resources.","avoid_when":"You need a managed hosted API with stable SLAs, turnkey authentication/authorization controls, or a clearly documented production-grade REST API surface.","last_evaluated":"2026-03-29T13:14:42.275799+00:00","has_mcp":false,"has_api":false,"auth_methods":[],"has_free_tier":false,"known_gotchas":["Harmony formatting/tools are required for correct model behavior; using raw generation without applying the harmony/chat template can lead to incorrect outputs","Reference implementations are primarily for educational purposes and may not be optimized for production reliability/performance","Triton/optimized backends may require specialized environment setup (nightly builds, CUDA/Triton toolchains); OOM guidance is limited to a specific PyTorch allocator setting"],"error_quality":0.0}