# Making local LLM + TTS work for a Persian voice assistant on a GTX 1650 Ti (4GB VRAM) — looking for advice > Source: > Published: 2026-09-17 20:19:40+00:00 Hi everyone, I’m building a real-time, two-way Persian voice conversation pipeline for a small robot project (Reachy Mini) with my professor. Current architecture: `fa-IR-FaridNeural` voice) — cloud-only **Why LLM/TTS ended up cloud-based:** I initially tried `qwen2.5:3b` locally via Ollama (CPU-only, since my venv’s torch build is CPU-only), but the output quality in Persian was poor — frequent code-switching into English/other languages, incoherent responses. Switching to Qwen2.5-72B via HF Inference API fixed this completely; responses are now coherent and consistently Persian. edge-tts also gives good voice quality. **The problem:** My internet connection is very slow and unstable (~0.7 Mbps down), so I’m getting periodic `ConnectTimeout` errors on the API calls (I’ve added retry logic, which helps but doesn’t eliminate the issue). For a robot that needs to work reliably, I’d like to move both LLM and TTS to fully local inference if possible. **My hardware:** **What I’m trying to figure out:** Any pointers to models, quantization strategies, or alternative local Persian TTS projects would be hugely appreciated. Happy to share more details (code, benchmarks) if useful. Thanks in advance!