Waveium vs Loops

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Waveium compared with Loops
Detail	Waveium	Loops
What it does	Wireless simulation through a single API	Python SDK for LoRA fine-tuning with supervised fine-tuning and reinforcement learning
Stage	Not given	Not given
Founded	Not given	Not given
Based in	SE	Not given
Pricing model	Paid	Not given
Pricing	from €35/month	Not given
Key features	Geometry-based stochastic channel modeling with ray tracing	forward_backward() operation for computing loss and accumulating gradients optim_step() for updating the adapter sample() for generating from current or saved policy save_state() to save and resume training state Tinker API compatibility Separate trainer and sampler resources Synchronous and asynchronous RL patterns Frozen base model weights with LoRA adapter updates Support for open models from Qwen, Google, DeepSeek, Moonshot AI, NVIDIA, and Z.ai
What makes it different	Minimal input required—rough sketch instead of complex environmental models Results validated against extensive measurement campaigns Proprietary algorithm developed and implemented by founders	Managed training and sampling infrastructure, no setup required Tinker-compatible API for easy migration Ready-made SFT and RL recipes through Loops cookbook Support for vision-language models
Community votes	0	0
DR (Domain Rating by Ahrefs)	6 no change since last check	77 no change since last check
Trust Flow (Majestic)	10	13
Citation Flow (Majestic)	11	43
Referring domains (Majestic)	15	550

3 details filled in for both companies.