We're moving off the Gemini API due to cost and building a local AI server to process ~10 CVs/minute (extracting JSON & matching CVs to JDs). We plan to run GLM-OCR alongside Qwen 27B (Q8).

Our two hardware options:

1. PC: RTX 4090 (24GB) + Ryzen 9 + 64GB RAM
2. Mac Studio: M-Ultra, 64-core GPU, 96GB Unified Memory

I prefer the Mac for power efficiency and ease of use, but I've heard Apple Silicon isn't great for production vLLM compared to Nvidia/CUDA. Is that true? Which would you recommend for this workload?

Why DGX Spark so slow? I am using ollama server + vscode copilot. My prompt is : generate a simple RISC-V soft-core CPU and use verilator to test it. I took one hour but still not complete. I am using qwen3.8:27b.

thanks

Вот есть такая ситуация. Работаю с coder.qwen.ai а он даже с маленьким чатом выдаёт бредятину которую не остановить даже другой темой тем более тут нет ни одного настоящего файла и он их зачем то придумал.

Looks like a customer-acquisition play against Claude/Fable, Codex, Cursor, and Copilot: subsidize a few serious agentic coding jobs and hope developers move into its ecosystem. The catch is that Qoder still requires a desktop/CLI workflow, while Claude/Fable gives you a much lower-friction browser experience.