Open Models Coding Essentials – Running LLMs Locally and in the Cloud Course
TL;DR
Andrew Brown tests open-source coding models including Gemma 4, Kimi 2.5, and Qwen across local and cloud deployments to evaluate viable alternatives to proprietary solutions, finding that while some models perform surprisingly well, hardware constraints make cloud hosting the practical choice for most developers.
🤖 Model Performance Benchmarks 4 insights
Kimi 2.5 leads open coding models
Kimi 2.5 demonstrated the most reliable tool use and agentic capabilities, outperforming GLM, MiniMax, and other competitors in practical coding tasks.
Gemma 4 shows promise but demands heavy hardware
Gemma 4 delivers surprisingly good performance with a small memory footprint, yet requires 24-32GB of VRAM and a 32,000 token context window to function effectively as a local coding assistant.
Qwen struggles with critical tool calling
Despite popularity for cost-effectiveness, Qwen 3.5 consistently failed at tool calling and required extensive manual plumbing to execute basic coding workflow actions.
GLM and MiniMax offer consistency
These models provided reliable but unexceptional performance across coding tasks, serving as viable alternatives for users prioritizing stability over peak capability.
💻 Infrastructure & Deployment Reality 3 insights
Local deployment requires expensive hardware
Effective local setups demand approximately $10,000 in equipment such as dual Mac Studio setups or custom rigs with 24-32GB VRAM, making local inference inaccessible for most users.
Ollama Cloud offers best subscription option
At $20-30 monthly, Ollama Cloud provides unquantized models with reliable performance and seamless integration, while cheaper alternatives serve highly quantized models that perform poorly.
GPU rental services remain inaccessible
Services like CoreWeave, Anyscale, and Lambda suffer from strict service quotas, lengthy sales processes, and inconsistent hardware availability that prevent reliable access.
🛠️ Coding Harness Integration 3 insights
Claude Code excels with open models
Claude Code demonstrated exceptional compatibility with open models via Ollama integration, outperforming specialized alternatives from startups like Kilo, Open Code, and Factory Droid.
PI coding agent prioritizes transparency
This barebones open-source harness allows developers to inspect underlying logic easily, though it intentionally lacks features like plan mode and MCP based on the creator's strong opinions.
Goose CLI targets enterprise adoption
Backed by the Linux Foundation for long-term maintenance guarantees, Goose CLI works well locally but proved difficult to configure with Ollama Cloud despite extensive troubleshooting.
Bottom Line
Use Claude Code paired with Ollama Cloud ($20-30/month) for reliable open-model coding, as local deployment requires prohibitively expensive hardware (24-32GB+ VRAM) and many alternative harnesses lack maturity or reliable tool-calling capabilities.
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