About this episode
James and Frank discuss the advantages of running AI coding models locally compared to in the cloud, exploring various tools and practical takeaways.
In this episode James and Frank dive into running AI coding models locally versus in the cloud—BYOK/Open Router, VS Code’s chat/agent harness, model runners (Olama, vLLM), and the practicality of 27B models on a 3090 using 4‑bit quantization. They share hands-on takeaways—how recent engineering (MT/MTPLX) boosts inference to usable token rates, when auto model selection makes sense, cost and hardware trade‑offs, and why local models can liberate your workflow while still needing smarter, unified tooling. Follow Us Frank: Twitter , Blog , GitHub James: Twitter , Blog , GitHub Merge Conflict: Twitter , Facebook , Website , Chat on Discord Music : Amethyst Seer - Citrine by Adventureface ⭐⭐ Review Us ⭐⭐ Machine transcription available on http://mergeconflict.fm Support Merge Conflict
People in this episode
Hosts: James, Frank
Topics covered
- AI coding models
- local vs cloud computing
- VS Code tools
- model runners
- hardware trade-offs
- workflow optimization
Keywords
- local LLMs
- AI models
- VS Code
- quantization
- inference
- model selection
- hardware
- workflow
Mentioned in this episode
Organizations: VS Code, Merge Conflict, Twitter, Blog, GitHub, Facebook, Discord
Products: Olama, vLLM, 27B models
Books & works: Amethyst Seer - Citrine
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- 515: Mini-LED, IPS, and the Great Monitor Rabbit Hole · May 18, 2026 · 44 min
- 513: Agents Over Chat: The Future of Developer Workflows · May 4, 2026 · 58 min
- 512: Does Matter Really Matter? · April 27, 2026 · 37 min
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