Qwen vs Llama for Local Agents: Which Models Pair Best with Friday?
When an assistant must route, plan, and act, model selection is an operations decision. Below is a practical comparison of Qwen and Llama families for local agents, especially with Open Friday.
Requirements beyond chat quality
- Reliable tool and plan following
- Acceptable latency within your VRAM budget
- A vision model that can interpret UI chrome
- Stable behavior across multi-step computer-use flows
Why Friday documentation defaults to Qwen
Open Friday’s recommended defaults include Qwen 3.5 chat tags and Qwen VL vision tags. In practice that provides:
- Strong instruction following for structured action plans
- Convenient Ollama tags at 4B and 9B size points
- Vision variants sized for desktop screenshots
For the shortest path to a working Friday setup, start with the documented Qwen set.
When Llama remains a strong option
Llama-class models remain appropriate for:
- Teams standardized on Meta’s ecosystem
- Fine-tunes you already maintain
- Chat-heavy workflows that do not require Friday’s VL defaults
You can point Ollama at Llama tags; re-validate computer-use quality afterward. Vision and UI grounding are typically where stacks diverge most.
Recommendation matrix
| Priority | Prefer |
|---|---|
| Fastest Friday setup | Qwen defaults from the repository |
| Existing Llama stack familiarity | Llama (validate agent steps carefully) |
| Coding assist (VRAM permitting) | Dedicated coder tags (for example, Qwen coder) |
| Screen automation | Qwen VL (or comparable VL) with hybrid UIA |
Summary
For Open Friday on Windows, Qwen presets are the supported defaults. Llama remains viable with additional tuning. Benchmark with real tasks — document summarization is not equivalent to multi-step desktop automation.
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