Compare AI tools

	Perplexity S	smol-audio A
Tagline	AI search done right. Cited answers, not chat theater.	A free, open collection of Colab notebooks that makes fine-tuning Whisper, Parakeet, Voxtral, Granite Speech, and Audio Flamingo 3 actually approachable on commodity GPUs.
Category	Research	Audio
Pricing	Free + $20/mo Pro	Free (open-source, Apache 2.0)
Best for	Replacing Google for any question where you want a cited answer in seconds.	ML engineers and audio researchers who want reproducible, low-friction recipes for fine-tuning open-source speech models on custom domains without standing up their own GPU infra.
Strengths	Sources every claim Fast, current answers Pro Search runs multi-step research Spaces for persistent context	Covers five distinct state-of-the-art audio models in one repo — rare breadth for a single toolkit Designed to run on a standard 16 GB Colab T4 GPU, no local hardware needed Exposes full training loops and data pipelines transparently within the HuggingFace ecosystem (transformers, peft, accelerate, datasets) LoRA support baked in for memory-heavy models like Audio Flamingo 3 and Voxtral Apache 2.0 license — fully hackable and production-ready
Weaknesses	Not a general chatbot Answers can be shallow on complex topics	No UI or web app — purely notebook-based, so non-developers need not apply Very new (released late April 2026), so community vetting, bug reports, and long-term maintenance are unproven Colab's free tier GPU availability is unreliable; longer fine-tuning runs may timeout or OOM without Colab Pro
Kai's verdict	S-tier for search. I use it before Google now. If you're still Googling everything, try this for a week.	If you've ever rage-quit trying to fine-tune Whisper on a niche language or domain, smol-audio is the cookbook you wished existed — transparent, practical, and actually runs on free Colab. It's a practitioner's toolkit, not a product, but that's exactly what makes it useful. (Verdict pending Phi's full review.)
Link	Open →	Open →