GPT-5.4 vs GPT-OSS 20B

1. Best Intelligence at Scale

• OpenAI positions GPT-5.4 as its frontier model for agentic, coding, and professional workflows.
• Built for complex professional work where stronger reasoning and higher answer quality matter.

2. Configurable Reasoning + Multimodal Input

• Supports configurable reasoning effort from none to xhigh, letting teams balance speed and depth.
• Accepts both text and image inputs while producing text output.

3. Massive Context for Long-Running Work

• 1.05M token context window supports very large codebases, documents, and multi-step workflows.
• Allows up to 128 k output tokens for long-form answers and larger generations.

4. Updated Knowledge & Broad Tool Support

• Knowledge cut-off of Aug 31 2025 keeps it current for newer frameworks and business context.
• Supports tools like web search, file search, code interpreter, hosted shell, computer use, and MCP in the Responses API.

• 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.
• 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.
• Adjustable reasoning effort: you can trade latency vs quality by tuning “reasoning effort” levels.
• Efficient hardware requirements (for its class): designed to run on a single 16 GB-class GPU or optimized local deployments for lower latency applications.
• 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.
• Flexibility: since weights are available, you can self-host, fine-tune, or deploy offline, giving more control than closed API models.