Reviews praise TensorZero’s easy setup, clean interface, and time-saving unified API for working across LLMs. Users highlight strong observability, A/B testing, and feedback-driven optimization that streamlines prompt and model tuning, with several noting smoother fine-tuning and reliable self-hosting options. While one comment felt oddly worded enthusiasm about metrics, overall sentiment is highly positive, citing speed, reliability, and helpful documentation. Makers of other products weren’t represented here, so no maker-specific comparisons were available. Teams building production-grade AI apps appear especially satisfied with its efficiency and focus.
Been looking for a better way to manage LLM experiments across providers, TensorZero nailed it. The A/B testing and prompt evals are super slick.
@gabrielbianconi Congratulations. And happy product launch.
TensorZero
@huisong_li Thanks for the support!
DeepTagger
Congratulations on your launch! I was hoping to see "Supervised Fine-Tuning" in action, but I guess the video had to be brief. Good luck with this project!
That's what I'm looking for and its open source to ! Best of luck team, for future. Just one question is there a way to checkout the remaining credits on a single dashboard like I'm switching to Anthropic dashboard to checkout the stats of credits ! Also can I use 2 models at same time.
TensorZero is an amazing product..
Thanks for launching this product...
Keep growing
TensorZero makes building and scaling LLM applications so much easier. One API for every model, built-in observability, optimization, and A/B testing — all open source. I love how quickly I could turn feedback and metrics into smarter, faster, cheaper models. Setup literally took minutes!
Agnes AI
Unifying all LLM providers into one super-fast API is just genius, tbh—no more hacky integrations or crazy latency. Open-source too? This is wild, team!
TensorZero
@cruise_chen Thank you! Hope this is helpful for Agnes AI.