271–280 of 616 posts
Pelicans for 3.6 Flash and 3.5 Flash-Lite (Cyber isn't available to me through the API yet.) https://tools.simonwillison.net/markdown-svg-renderer#url=ht...
I am growing tired of these pelicans posts every time a new model is published. Feels to me like low effort personal brand promotion. Just sharing my 2 cents.
Google somehow managed to snatch defeat from the jaws of success with their AI products. They literally forced me and my company out of Antigravity by phasing out AI Ultra subscription without any proper product follow-up. Antigravity IDE cannot even have poweruser subscriptions now from Google Workspace an Gemini Enterprise Agent Platform cannot be attached to Antigravity IDE. Gemini Enterprise Agent Platform has an…
Aren’t the subscriptions extremely subsidized and burning cash for Anthropic and OpenAI? A reasonable explanation is they’re simply abstaining from the war of attrition, especially given cheaper comparable models are breaking the illusion that the “frontier of intelligence” has any kind of per token margin.
And the real numbers could be better for Anthropic. It's feasible Opus models are actually cheaper to serve than GLM 5.2 because Anthropic have optimized the hell out of inference.
I wonder how big the Pro model is that Google is using behind the scenes to train these smaller ones. Going on baseless speculation, the lack of accompanying pro models with these flash releases either means: 1) the model is too big to be economical, 2) google doesn't have the compute to serve the big model, 3) their big model has too many alignment issues to serve to the public. edit: looks like benchmarks are up on…
Logan Kilpatrick said on an interview not too long ago that flash 3 and 3.5 are the same pre-train. all gains on top of 3 flash are post-training
Earlier quoted context omitted.
It's absolute insanity. They have all the resources to have been able to lead from the front with this new technology. They have the products and users to integrate this technology into people's already existing lives. But they keep fumbling. They're not even benchmarking against other models now, just against themselves - which tells you everything you need to know.
What does "leading from the front" get them? There is absolutely no loyalty when it comes to coding. Nothing could be more common than people threating to jump ship whenever another frontier or open source model comes. Google is clearly able to keep growing their free and consumer and small business use cases. Unlike corporate coding, we actually have evidence that solo and small businesses can actually see productiv…
Earlier quoted context omitted.
Aren’t the subscriptions extremely subsidized and burning cash for Anthropic and OpenAI? A reasonable explanation is they’re simply abstaining from the war of attrition, especially given cheaper comparable models are breaking the illusion that the “frontier of intelligence” has any kind of per token margin.
Makes sense, subsidizing tokens doesn’t seem like a great strategy for a public company.
It's scary relying on Google's models. I have a very price sensitive workload that used to run on flash 2.5 lite - it's deprecated now. The replacement 3.1 flash lite is a lot more expensive, but now also has a sunset date. 3.5 flash lite is even more expensive. So the price is rising and you have no choice but to keep paying more and more.
Just switch the model, its not that much effort tbh. And u can also get a cheaper model than 2.5 lite for the same intelligence
For my use case, `gemini-3.1-flash-lite` is ~20% higher accuracy than the next best model of comparable cost (considering both proprietary and open-weight alternatives)
It's a bit disheartening to see no comparison to other models here - and I'm not sure this pushes the curve anywhere. 3.6 flash is more expensive than GLM 5.2 - but seemingly worse, although this post is really light (lite?) on details. It seemed for a time that Google had finally gotten the ball rolling, but I'm doubting that more and more as time passes. We'll see what happens with 3.5 pro I suppose.
It’s really surprising. When Apple announced the multi-billion dollar deal with Google to power Apple Intelligence I thought great things were coming. Instead we are getting more and more bad news: delayed Pro models and AI leadership leaving. I wonder if Apple know something the rest of us don’t know or if they are already regretting their decision.
Pelicans for 3.6 Flash and 3.5 Flash-Lite (Cyber isn't available to me through the API yet.) https://tools.simonwillison.net/markdown-svg-renderer#url=ht...
The fish and the cap where always added when I asked an llm to improve it's first attempt.
This continues the trend in LLM progress of better=more stuff
Edit: I wonder if this is a function of the reasoning training, where more tokens/ stuff is rewarded.