HN user
https://fikrikarim.com
This repo is a good starting point for comparing TTS models https://github.com/5uck1ess/tts-bench
Kokoro is a really good model, considered it’s released 1.5 years ago. It’s punching above its weight https://5uck1ess.github.io/tts-bench/scores.html
I've been using Zed for a few weeks now and these two are also my main complaints as well.
Oh yeah for sure. At that point, using SES is probably a better option compared to running a VPS just for SMTP. I posted that to let them know that SMTP support is a requirement for some developers.
Ok I just tried the service since I want to migrate from Resend.
Seems like you can only send email via the worker or REST API for now?
Can I send via SMTP? I'm using Supabase and it needs the SMTP credentials.
I can't find anything on the dashboard or on the docs, even though last year they said it supports SMTP [0]
Related: Gemma 4 on iPhone (254 comments) - https://news.ycombinator.com/item?id=47652561
This is an interesting approach.
How does this compare to Next.js App Router?
Next.js App Router is server-first: your component tree lives on the server by default, and you opt into client interactivity with 'use client'.
TanStack Start is isomorphic-first: your tree lives wherever makes sense. At the base level, RSC output can be fetched, cached, and rendered where it makes sense instead of owning the whole tree. When you want to go further, Composite Components let the client assemble the final tree instead of just accepting a server-owned one.
The sudden server-first change on Next.js App Router definitely trips some people, especially since React started as client-only library.
Well, on my demo it's around 2.5s and I already consider it as a "real-time". One way to improve it is to disable the image input.
What's your average response time with M1 max and what's the target?
Is this the problem? https://news.ycombinator.com/item?id=47669954
In the /r/macapps subreddit, they have huge influx of new apps posts, and the "whisper dictation" is one of the most saturated category. [0]
“Compare” - This is the most important part. Apps in the most saturated categories (whisper dictation, clipboard managers, wallpaper apps, etc.) must clearly explain their differentiation from existing solutions.
https://www.reddit.com/r/macapps/comments/1r6d06r/new_post_r...
During my limited testing, it works better than I expected at handling multiple languages in a single session. Perhaps I just had a low expectation since I've mostly worked with English-only STT models.
Nothing unique, it's just taking a snapshot when it's processing the input. Even processing a single image will increase the TTFT by ~0.5s on my machine, so for now, it seems to be impossible for feeding a live video and expecting a real-time response.
In regards to the video capability, I haven't tested it myself, but here's a benchmark/comparison from Google [0]
Huh that's weird. I just tried it and it works on my machine. Could you perhaps create a GitHub issue and share the reproduction steps and any relevant logs?
This. I posted this on my other comment, but there's a meme that "Gen Z Kids Don't Understand How File Systems Work" [0].
There seems to be a disconnect between some developers and the younger folks.
This is my stance as well, but keep in mind that a lot of people have the opposite preference.
They didn't grow up with the world wide web. They only started using technology when Android and iPhone was popular. They only know Whatsapp, Youtube, TikTok. They're not used to using the browser.
There's a meme that "Gen Z Kids Don't Understand How File Systems Work" [0]
So, it'll depend on your target audiences.
Oh wow, that's awesome. Thanks a lot, dang!
Thank you. This reminds me of a paragraph from the LatentSpace newsletter [0]
The excellent on device capabilities makes one wonder if these are the basis for the models that will be deployed in New Siri under the deal with Apple….
https://www.latent.space/p/ainews-gemma-4-the-best-small-mul...
Thanks for sharing! I'm still torn about it. Sure it'll feel more natural if you have the AI head animation, but I don't want people to get attached to it. I don't want to make the loneliness epidemic even worse.
Thanks! Although, I can't claim any credit for it. I just spent a day gluing what other people have built. Huge props to the Gemma team for building an amazing model and also an inference engine that's focused for edge devices [0]
This app is cool and it showcases some use cases, but it still undersells what the E2B model can do.
I just made a real-time AI (audio/video in, voice out) on an M3 Pro with Gemma E2B. I posted it on /r/LocalLLaMA a few hours ago and it's gaining some traction [0]. Here's the repo [1]
I'm running it on a Macbook instead of an iPhone, but based on the benchmark here [2], you should be able to run the same thing on an iPhone 17 Pro.
[0] https://www.reddit.com/r/LocalLLaMA/comments/1sda3r6/realtim...
[1] https://github.com/fikrikarim/parlor
[2] https://huggingface.co/litert-community/gemma-4-E2B-it-liter...
Update: Just made one that runs on Macbook M3 Pro https://github.com/fikrikarim/parlor
Nice project. I thought of building exactly this.
Since it's much easier to port source code to other languages now, I'd love to see more projects like written in Swift, or C#.
The big question is whether Apple can keep shipping new models constantly.
AFAIK the current model is on par with with Qwen-3-4B, which is from a year ago [0]. There's a big leap going from last year Qwen-3-4B to Qwen-3.5-4B or to Gemma 4.
Apple model is nice since you don't need to download anything else, but I'd rather use the latest model than to use a model from a year ago.
https://machinelearning.apple.com/research/apple-foundation-...
Thank you for the kind words!
Ok it's on the app store now: https://apps.apple.com/app/volocal/id6761493288
I'm curious about the multimodal capabilities on the E2B and E4B and how fast is it.
In ChatGPT right now, you can have a audio and video feed for the AI, and then the AI can respond in real-time.
Now I wonder if the E2B or the E4B is capable enough for this and fast enough to be run on an iPhone. Basically replicating that experience, but all the computations (STT, LLM, and TTS) are done locally on the phone.
I just made this [0] last week so I know you can run a real-time voice conversation with an AI on an iPhone, but it'd be a totally different experience if it can also process a live camera feed.
In the coming days, we will also open-source smaller-scale variants, reaffirming our commitment to accessibility and community-driven innovation.
This is huge problem for developing countries. Most people here have $100-$200 phones. iPhone is a luxury.
Do you think it the models you’re using could be quantized more that they could be downloaded on first run using Background Assets?
I first tried the Qwen 3.5 0.8B Q4_K_S and the model couldn't hold a basic conversation. Although I haven't tried lower quants on 2B.
I'm also interested on the Apple Foundation models, and it's something I plan to try next. AFAIK it's on par with Qwen-3-4B [0]. The biggest upside as you alluded to is that you don't need to download it, which is huge for user onboarding.
[0] https://machinelearning.apple.com/research/apple-foundation-...
The Github repo is only for issue tracker