Launch Intel
Ya

YamChat – Chat with Multiple LLMs from one location

Hacker News

YamChat – Chat with Multiple LLMs from one location

Hey! I'm Chris. I got tired of opening multiple tabs to chat with different LLMs, so I built YamChat to solve that. You can talk to multiple LLMs from one place. One of the standout features, and the main reason I built YamChat, is you can ask a question to multiple LLMs in parallel. For technical questions I rarely trust just one LLM. I was getting tired of opening multiple tabs to ask the same question to various models, so I consolidated all of that into one location - YamChat. I also didn’t like paying for multiple LLMs. I wanted to be able to pay one price that gave me access to everything, which YamChat also provides. I've built it using NextJs and Convex, with WorkOs for auth and Polar for payments. It's still pretty bare bones so I would love pressure testing! The free tier is admittedly pretty small, so if you run out of credits and want to give it a solid go shoot me an email, I'd be happy to make you a discount code for a free month. Let me know what you think!

Visit productView on Hacker NewsSep 17, 2025
Share card

Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, email · Missing: mac, agents, macos
86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month, para · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Mo
ModelMashup – Chat with Multiple LLMs Simultaneously32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ModelMashup – Chat with Multiple LLMs Simultaneously

Hacker News1
Ca
Call Multiple LLMs with GraphQL and AI Chainer42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Call Multiple LLMs with GraphQL and AI Chainer

Hacker News2
In
IncarnaMind-Chat with your multiple docs using LLMs52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

IncarnaMind-Chat with your multiple docs using LLMs

Hacker News57
He
Herd location+interest based chat39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Herd location+interest based chat

Hacker News2
Po
Pokemon Sniffer – Rarest Pokemon Location56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Pokemon Sniffer – Rarest Pokemon Location

Hacker News1
Lo
Location Chatroom44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Location Chatroom

Hacker News1
La
LazyScout - Zipcar for location scouting44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LazyScout - Zipcar for location scouting

Hacker News3
LL
LLM Council – Run multiple LLMs with critique and consensus eval52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

LLM Council – Run multiple LLMs with critique and consensus eval

Hacker News4
bandleader.ai
bandleader.ai38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Determines the best answer for you across multiple LLMs

Product Hunt+6
Mu
Multiple invitations on top of devise_invitable (RoR)38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Multiple invitations on top of devise_invitable (RoR)

Hacker News1
Browse all productsAnalyze your launch