GPT-OSS 20B vs Claude 4.5 Haiku

• 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.

1. Frontier-level coding at small-model speed

• Similar coding performance to Claude Sonnet 4 at one-third the cost.
• Runs 4-5x faster than Sonnet 4.5 for many tasks.
• Ideal for real-time pair programming, prototyping, and rapid iteration.

2. Excellent computer-use abilities

• Surpasses Claude Sonnet 4 in certain computer-control tasks.
• Great for agents requiring low-latency tool use (Chrome automation, coding agents, etc.).

3. Perfect for real-time, low-latency applications

• Chat assistants
• Customer support agents
• Interactive development loops
• Multi-agent orchestration

4. Works seamlessly with Sonnet 4.5 in hybrid agent setups

• Sonnet 4.5 plans complex workflows.
• Haiku 4.5 executes subtasks in parallel for speed and cost-efficiency.

5. High alignment & safest Claude model by metric

• Lower misaligned behavior rates than Haiku 3.5, Sonnet 4.5, and Opus 4.1.
• Limited CBRN risk → released under AI Safety Level 2 (ASL-2).