{"id":"openai-gpt-oss","name":"gpt-oss","homepage":"https://openai.com/open-models","repo_url":"https://github.com/openai/gpt-oss","category":"ai-ml","subcategories":[],"tags":["ai-ml","llm","open-weight-models","inference","local","tool-calling","harmony","vllm","triton","metal","hugging-face"],"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.","use_cases":["Run gpt-oss open-weight models locally for experimentation or prototyping","Integrate the harmony response format and model tools (browser/python) into an application","Spin up an OpenAI-compatible server using vLLM for development workloads","Test different inference backends (Transformers, vLLM, PyTorch reference, Triton reference, Metal reference)","Use the provided terminal chat and example server as starting points for agentic workflows"],"not_for":["Production deployment of the reference PyTorch/Triton/Metal implementations (explicitly described as reference/educational)","Environments where you cannot meet heavy GPU/compute requirements for large models (noted for reference code)","Use cases that require a supported formal OpenAPI/SDK experience for programmatic integration (primarily local/in-repo usage)"],"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.","alternatives":["vLLM OpenAI-compatible server with open-weight model(s) from Hugging Face (where available)","Ollama or LM Studio for simplified local model running (where supported)","Other open-weight LLM repos that provide production-ready server endpoints and SDKs"],"af_score":40.0,"security_score":18.8,"reliability_score":26.2,"package_type":"skill","discovery_source":["openclaw"],"priority":"high","status":"evaluated","version_evaluated":null,"last_evaluated":"2026-03-29T13:14:42.275799+00:00","interface":{"has_rest_api":false,"has_graphql":false,"has_grpc":false,"has_mcp_server":false,"mcp_server_url":null,"has_sdk":false,"sdk_languages":[],"openapi_spec_url":null,"webhooks":false},"auth":{"methods":[],"oauth":false,"scopes":false,"notes":"The README describes local/offline inference and reference servers/examples; no concrete hosted authentication mechanism is documented for the repository itself."},"pricing":{"model":null,"free_tier_exists":false,"free_tier_limits":null,"paid_tiers":[],"requires_credit_card":false,"estimated_workload_costs":null,"notes":"This is a self-hosted/reference repo; costs depend on hardware and any external hosting you choose (e.g., running vLLM servers)."},"requirements":{"requires_signup":false,"requires_credit_card":false,"domain_verification":false,"data_residency":[],"compliance":[],"min_contract":null},"agent_readiness":{"af_score":40.0,"security_score":18.8,"reliability_score":26.2,"mcp_server_quality":0.0,"documentation_accuracy":55.0,"error_message_quality":0.0,"error_message_notes":null,"auth_complexity":100.0,"rate_limit_clarity":0.0,"tls_enforcement":0.0,"auth_strength":0.0,"scope_granularity":0.0,"dependency_hygiene":45.0,"secret_handling":60.0,"security_notes":"No hosted API authentication guidance is provided because the repo is primarily self-hosted/local inference. The README includes example server usage but does not document security controls such as TLS enforcement, authN/authZ, or safe tool sandboxing. The dependency list (from the manifest) includes common web/server libraries (FastAPI/uvicorn, requests/aiohttp), but no explicit security posture (SCA, pinned versions, CVE status) is available in the provided content.","uptime_documented":0.0,"version_stability":40.0,"breaking_changes_history":30.0,"error_recovery":35.0,"idempotency_support":"false","idempotency_notes":null,"pagination_style":"none","retry_guidance_documented":false,"known_agent_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"]}}