gpt-oss-20b

For developers seeking a balance between high-performance reasoning and deployment flexibility, gpt-oss-20b offers a compelling middle ground. Built on a Mixture-of-Experts (MoE) architecture, this 21B parameter model utilizes only 3.6B active parameters per token, significantly reducing inference latency and compute overhead without sacrificing the depth of a larger dense model. The Apache 2.0 license makes it an ideal candidate for commercial applications where data sovereignty and local hosting are priorities. With a massive 131k context window, it excels at long-form document analysis, complex codebase reasoning, and multi-turn conversational agents. Compared to standard dense models of similar size, you'll notice much higher throughput, making it particularly effective for scaling RAG pipelines or real-time agentic workflows where cost-per-token and speed are critical constraints.