411–420 of 692 posts
The pelican is a lot : https://github.com/simonw/llm-gemini/issues/133#issuecomment... Not a great bicycle though, it forgot the bar between the pedals and the back wheel and weirdly tangled the other bars. Expensive too - that pelican cost 13 cents: https://www.llm-prices.com/#it=11&ot=14403&sel=gemini-3.5-fl...
Given your pelican is very famous now, don't you think they are adding instructions to beat this benchmark those days?
The pelican is a lot : https://github.com/simonw/llm-gemini/issues/133#issuecomment... Not a great bicycle though, it forgot the bar between the pedals and the back wheel and weirdly tangled the other bars. Expensive too - that pelican cost 13 cents: https://www.llm-prices.com/#it=11&ot=14403&sel=gemini-3.5-fl...
This is a perfect illustration of something I noticed with llm progress. Ask them to improve an svg like this, and it never fixes the missing crossbar or disconnected limbs, it just adds more stuff. In this example they have obviously improved greatly, and it contains a ridiculous amount of detail, but they still to get the basic shape of the frame wrong. It's weird. And the pattern shows up everywhere, try it with a…
Earlier quoted context omitted.
We're having DeepSeek moments every couple of weeks. Qwen 3.6 hit hard in the self-hosting space. It's incredibly capable for its size, really shaking up what's possible in 64GB or even 32GB of VRAM. The Prism Bonsai ternary model crams a tremendous amount of capability into 1.75GB. And, DeepSeek V4 is crazy good for the price. They're charging flash model prices for their top-tier Pro model, which is competitive wit…
> It's incredibly capable for its size, really shaking up what's possible in 64GB or even 32GB of VRAM. You can lower that to at least 24GB. I've been running Qwen 3.5 and 3.6 with codex on a 7900 XTX and the long horizon tasks it can handle successfully has been blowing my mind. I would seriously choose running my current local setup over (the SOTA models + ecosystem) of a year ago just based on how productive I can…
Earlier quoted context omitted.
in any corporate or half compliance-relevant setting switching isn't trivial. new DPA, subprocessor notifications, TIA, procurement review, security questionnaires, plus re-running your evals because prompts don't transfer 1:1. token cost is just one of the line items.
no it really not, even the soggiest bank has multiple api vendors atm.
From what I hear, most enterprise AI deployments are seat-based subscriptions with annual commitments.
Per million input/output tokens: Gemini 2.5 flash: $0.30/$2.50 Gemini 3.0 flash preview: $0.50/$3.00 Gemini 3.5 flash: $1.50/$9.00 Interesting pricing direction. I don't think we have ever seen a 3x price increase for in the immediate next same-sized model (and lol @ 3 only ever getting a preview). 3.5 flash costs similar to Gemini 2.5 pro which was $1.25/$10
Gen AI is unprofitable, especially at the insanely cheap rates they've been offering to get people in the door. So expect more increases in the future.
The pelican is a lot : https://github.com/simonw/llm-gemini/issues/133#issuecomment... Not a great bicycle though, it forgot the bar between the pedals and the back wheel and weirdly tangled the other bars. Expensive too - that pelican cost 13 cents: https://www.llm-prices.com/#it=11&ot=14403&sel=gemini-3.5-fl...
Love your pelicans, as always. And that one is... Wow. I noticed the "Synthwave" aesthetic, which is enjoying quite some success since quite some time now, has found its way into AI models (even when it's not in the user's query). It's not the first time I see the sun at sunset with color bands etc. in AI-generated pictures. Don't know why it's now taking on in AI too. https://en.wikipedia.org/wiki/Synthwave Hence th…
Earlier quoted context omitted.
We have Qwen 3.6-35b (6) on a 5090 (32GB) and it's blowing me away. Works fine for most (not all) code generation tasks. One developer here has been extremely stubborn about adopting AI; he's finally adopted it, albeit only when it's coming from a local model like this. DeepSeek V4 Pro likewise is insanely good for the price. I simply point it at large codebases, go get a cup of coffee or browse Hacker News, and then…
Any chance you'd be willing to talk further about your setup? I have 2 x 3090s in a local machine, and I'm still left with questions about how best to use stuff locally.
Earlier quoted context omitted.
If Google is actually getting cheaper inference than everyone else with their TPUs, this smells like trouble to me. Maybe serving LLMs at a profit is proving difficult. Or maybe they think because their benchmarks are good they can ramp up the prices. Seems like they don’t have the market share to justify a move like that yet to me.
Prevailing wisdom is that serving LLMs at a profit is achievable... it's when you factor in the cost of training them that prices get astronomical real fast. Open-source model inference providers (who do not have to bear the cost of training) seem able to do it at much lower prices. https://www.together.ai/pricing https://fireworks.ai/pricing#serverless-pricing (scroll down to headline models) Of course, it's possibl…
I think you're right that releasing models at a slower cadence would bring down costs to some degree, but it's not clear how much. All of these companies could significantly reduce their opex but at the risk of falling behind in terms of being at the frontier.
The pelican is a lot : https://github.com/simonw/llm-gemini/issues/133#issuecomment... Not a great bicycle though, it forgot the bar between the pedals and the back wheel and weirdly tangled the other bars. Expensive too - that pelican cost 13 cents: https://www.llm-prices.com/#it=11&ot=14403&sel=gemini-3.5-fl...
That's not to say I don't spend my days raging at it... a lot... but it's not that bad. It does tend to ignore completion criteria but it doesn't obviously degrade when being nudged like some models do.
Google also updated Antigravity. version 2.0 is more for conversation with agent. The previous VS Code like IDE was much better.