Open-Weight Models Closing the Gap: GPT-OSS, Qwen3, Llama 4

Open-weight coding models are improving fast. This guide covers what is available and when they can replace or complement closed models.

Quick Answer

Open-weight models (DeepSeek Coder, Qwen3, Codellama, Llama 4–based, etc.) run locally or on your infra. For many coding tasks they are competitive with closed models; for complex reasoning the gap remains. Use them for privacy, cost control, and customization. See Ollama, Continue, and our open-source tools guide.

Open vs Closed: The Gap

Leading Open-Weight Coding Models

Availability depends on Ollama, Hugging Face, and your hardware. Check model cards for requirements.

When Open-Weight Makes Sense

How to Run Them

• Ollama: ollama pull deepseek-coder-v2; use with Continue, Aider, or Cline.
• vLLM, llama.cpp: For API-compatible servers to use with Cursor BYO.
• Hugging Face: Download and run with Transformers or compatible runtimes.

See Ollama + Continue private setup for a full local workflow.

The Trajectory

Open-weight models have improved sharply in the last year. For standard coding tasks, the difference from closed models is often small. For cutting-edge reasoning or very long context, closed models still lead. That gap is likely to narrow further; worth re-evaluating periodically.

Next Steps

• Best open-source AI coding tools — OSS tools.
• ollama-continue-private-setup">Ollama + Continue private setup — Local setup.
• Privacy-First collection — Tools with strong data controls.