DeepSeek v4
261–270 of 1001 posts
Re: DeepSeek v4
#262For comparison on openrouter DeepSeek v4 Flash is slightly cheaper than Gemma 4 31b, more expensive than Gemma 4 26b, but it does support prompt caching, which means for some applications it will be the cheapest. Excited to see how it compares with Gemma 4.
Re: DeepSeek v4
#263> pricing "Pro" $3.48 / 1M output tokens vs $4.40 I’d like somebody to explain to me how the endless comments of "bleeding edge labs are subsidizing the inference at an insane rate" make sense in light of a humongous model like v4 pro being $4 per 1M. I’d bet even the subscriptions are profitable, much less the API prices. edit: $1.74/M input $3.48/M output on OpenRouter
Re: DeepSeek v4
#264Re: DeepSeek v4
#265Earlier quoted context omitted.
Weights are the source, training data is the compiler.
You got it the wrong way round. It's more akin to. 1. Training data is the source. 2. Training is compilation/compression. 3. Weights are the compiled source akin to optimized assembly. However it's an imperfect analogy on so many levels. Nitpick away.
Re: DeepSeek v4
#266Is V4 still not a multi-modal model?
Re: DeepSeek v4
#267> pricing "Pro" $3.48 / 1M output tokens vs $4.40 I’d like somebody to explain to me how the endless comments of "bleeding edge labs are subsidizing the inference at an insane rate" make sense in light of a humongous model like v4 pro being $4 per 1M. I’d bet even the subscriptions are profitable, much less the API prices. edit: $1.74/M input $3.48/M output on OpenRouter
Re: DeepSeek v4
#268I like the pelican I got out of deepseek-v4-flash more than the one I got from deepseek-v4-pro. https://simonwillison.net/2026/Apr/24/deepseek-v4/ Both generated using OpenRouter. For comparison, here's what I got from DeepSeek 3.2 back in December: https://simonwillison.net/2025/Dec/1/deepseek-v32/ And DeepSeek 3.1 in August: https://simonwillison.net/2025/Aug/22/deepseek-31/ And DeepSeek v3-0324 in March last year:…
This is just a random thought, but have you tried doing an 'agentic' pelican? As in have the model consider its generated SVG, and gradually refine it, using its knowledge of the relative positions and proportions of the shapes generated, and have it spin for a while, and hopefully the end result will be better than just oneshotting it. Or maybe going even one step further - most modern models have tool use and image…
I should try it again with the more recent models.
Re: DeepSeek v4
#269Earlier quoted context omitted.
American companies want a scan of your asshole for the privilege of paying to access their models, and unapologetically admit to storing, analyzing, training on, and freely giving your data to any authorities if requested. Chinese ulteriority is hypothetical, American is blatant.
It’s not remotely hypothetical you’d have to be living under a rock to believe that. And the fusion with a one-party state government that doesn’t tolerate huge swathes of thoughtspace being freely discussed is completely streamlined, not mediated by any guardrails or accountability. This “no harm to me” meme about a foreign totalitarian government (with plenty of incentive to run influence ops on foreigners) hooveri…
yes, this is exactly what I'm saying.
Re: DeepSeek v4
#270I like the pelican I got out of deepseek-v4-flash more than the one I got from deepseek-v4-pro. https://simonwillison.net/2026/Apr/24/deepseek-v4/ Both generated using OpenRouter. For comparison, here's what I got from DeepSeek 3.2 back in December: https://simonwillison.net/2025/Dec/1/deepseek-v32/ And DeepSeek 3.1 in August: https://simonwillison.net/2025/Aug/22/deepseek-31/ And DeepSeek v3-0324 in March last year:…
I think the pelican on a bike is known widely enough that of seizes to be useful as a benchmark. There is even a pelican briefly appearing in the promo video of GPT-5, if I'm not mistaken https://openai.com/gpt-5/ . So the companies are apparently aware of it.