GPT-5.2 vs GPT-OSS 20B

1. Advanced Reasoning for Diverse Domains

• Built to tackle coding and agentic workflows across multiple industries, with configurable reasoning support.

2. Multi-Modal & Long-Form Capabilities

• Handles both text and image inputs, producing text output:contentReference[oaicite:1]{index=1}.
• Allows up to 128 k output tokens for lengthy responses:contentReference[oaicite:2]{index=2}.

3. Large Context & Updated Knowledge

• 400 k token context window accommodates extensive codebases or documents:contentReference[oaicite:3]{index=3}.
• Knowledge cut-off of Aug 31 2025 keeps it current with recent developments:contentReference[oaicite:4]{index=4}.

• Open-weight / Apache 2.0 licensed: you can use, modify, and deploy freely (commercially & academically) under permissive terms.
• Large model size (≈ 21B parameters) with Mixture-of-Experts (MoE) architecture: only ~3.6B parameters active per token, yielding efficient inference. :contentReference[oaicite:1]{index=1}
• Very long context window support: up to ~128 K tokens (or ~131 K tokens per some sources) enabling in-depth reasoning, long documents, or multi-turn context. :contentReference[oaicite:2]{index=2}
• Adjustable reasoning effort: you can trade latency vs quality by tuning “reasoning effort” levels. :contentReference[oaicite:3]{index=3}
• Efficient hardware requirements (for its class): designed to run on a single 16 GB-class GPU or optimized local deployments for lower latency applications. :contentReference[oaicite:4]{index=4}
• Strong for tasks such as reasoning, tool-use, structured output, chain-of-thought debugging: because the model is open and you can inspect its chain of thought. :contentReference[oaicite:5]{index=5}
• Flexibility: since weights are available, you can self-host, fine-tune, or deploy offline, giving more control than closed API models. :contentReference[oaicite:6]{index=6}