# What is the "Best LLM for Shenava-Koochik ASR"

> Source: <https://discuss.huggingface.co/t/what-is-the-best-llm-for-shenava-koochik-asr/180530#post_2>
> Published: 2026-09-16 17:28:31+00:00

Worth noting Shenava-Koochik itself is a 114M Persian streaming ASR model (from Reza2kn’s Shenava collection), so ASR shouldn’t be the compute bottleneck here, the LLM stage is where “disition” (decision/intent understanding) is failing.

For Persian-language intent/decision-making specifically, general multilingual models like Qwen2.5 or Gemma tend to do noticeably better in Farsi than most “small” English-first models, that’s usually the actual fix rather than the ASR choice. If you want something Persian-specialized instead, `PartAI/Dorna-Llama3-8B-Instruct` is fine-tuned specifically for Persian instruction-following and reasoning. If you’re running this on Reachy Mini’s onboard Pi, 8B is probably too heavy for real-time local inference though, you’d want a smaller Qwen2.5 (1.5B/3B) or route the LLM call to HF Inference API/Endpoints instead of running it on-device, keeping ASR local and offloading only the decision step.