Edge Impulse vs Together AI

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Edge Impulse Fine-tuning	Together AI Fine-tuning
Tagline	End-to-end platform for training and deploying ML models on microcontrollers, sensors, and other edge hardware.	Fine-tune & serve open-weight models (Llama, Mistral, DeepSeek).
Category	Fine-tuning	Fine-tuning
Pricing	Freemium· Free developer tier; paid Professional and Enterprise plans (contact sales)	Paid· Pay-per-token; fine-tuning per-token
Model	Multi-model (TF Lite Micro, custom DSP blocks)	Llama / Mistral / Qwen / DeepSeek and others
Editorial score	—	8.6 / 10
Use cases	edge-aitinymlsensor-classificationcomputer-visionpredictive-maintenanceaudio-keyword-spotting	open modelsfine-tuninginference
Pros	Real end-to-end pipeline from data ingest to flashable firmware Broad hardware support across MCUs, NPUs, and gateways Strong DSP + ML workflow for time-series and audio Free tier is usable for serious prototyping Backed by Qualcomm with deep silicon partnerships	Wide open-model catalogue Competitive inference pricing Fine-tune + serve in one place Dedicated endpoints for production
Cons	Pricing for Professional/Enterprise tiers is opaque without a sales call Best-tuned outputs lean toward partner silicon Less useful if you're not targeting constrained devices	Latency varies by model Less polish than OpenAI
Website	edgeimpulse.com	www.together.ai

Pick Edge Impulse if

Pick Together AI if