Models that people like the design aesthetic of (Claude, GLM) tend to do better in LMArena than they do on other benchmarks. Design matters, but you look at a model like GPT-5.5 and it's behind Kimi K2.6, Sonnet 4.6, Qwen3.7 Max, and GLM-5.1 on LMArena's code leaderboard. Then you look at benchmarks like DeepSWE and GPT-5.5 blows them out of the water with only Fable and GPT-5.6 beating it.

I'm not saying that the LMArena leaderboard isn't useful, but I'm not sure how much weight I'd give it as a "code" leaderboard. I think often times it's a design comparison of simple front-end React apps rather than a coding comparison. GLM-5.2 is a very good model, but when you look at DeepSWE or Terminal-Bench v2, GPT-5.5 is well ahead.

At this point, I always look at things like Artificial Analysis' total cost to run their tests. It'll take into consideration the cost of tokens, how many tokens it burns through, and how effectively it uses caching (and the price of that caching).

If a model "costs the same" but its reasoning ends up going through a ton more tokens, it doesn't really cost the same in real world usage.

I feel like the "something new" was price. Over time, that price kept creeping up. Yes, it went from being a 95% flagship to being a 100% flagship, but it also went from being half price to full price.

It was also cool that it used Cyanogenmod which meant you got a community OS that actually got updates, but over time other manufacturers started offering updates for their phones (rather than abandoning them soon after manufacturing). And that was something new other than price. But I think the big thing was that it was a half-price phone when it launched. In 2014, it was just such an amazing deal. Today, it's the same price as Samsung phones.

- Telegram had usernames in 2014 before Signal added them a decade later, allowing people to chat without sharing their phone number

- Telegram has unencrypted chats which allow for giant chat rooms of 200,000+ and channels with millions of subscribers. Signal warns about performance issues when you have more than 150 people in a group. Telegram isn't just a messenger - it's often used as a social publishing platform like Instagram.

I don't use Telegram and use Signal a lot, but I also understand why other people use Telegram: the same reason they use Instagram.

Cursor's benchmark finds that Cursor's model (Composer 2.5) is basically as good as Opus 4.8 max and GPT-5.5 xhigh, but at a fraction of the price.

Artificial Analysis' testing shows Composer 2.5 to be pretty far behind: https://artificialanalysis.ai/agents/coding-agents. You look at the DeepSWE benchmark (which is probably the hardest to game at this point) and GPT-5.5 xhigh gets a 64, Opus 4.8 max gets 56, and Cursor 2.5 gets 16.

I don't doubt that Cursor works well for some people. It's beating DeepSeek v4 Pro in the DeepSWE benchmark and that's a very capable model. But I'm skeptical of the claims that it's a competitor for Opus 4.8 and GPT-5.5. It just seems convenient that their model does so well on their own benchmark while third party benchmarks have it far behind. Maybe it's a really great benchmark and a better measure than third party ones - I'd love for a cheap model to do as well as the expensive ones.

It's not simply marketing since the Pro/Max chips of a generation use the same cores as the regular version, just more of them or different combinations of performance and efficiency cores.

They hold the keys for your DID. If they don't allow you to move to another PDS, you can't move. The original theory was that you'd hold the private keys, but that's something that would hugely limit adoption so they decided to hold the keys themselves.

In terms of moving your backlog of posts to a new server, part of the issue is liability (not merely legal liability, but reputational as well). When you have a user on your platform and they're posting stuff, you're moderating them in real time. If they turn out to be a horrible troll, you've get the reports. Let's say a horrible troll has been on EvilServer and EvilServer has been ignoring the reports against them. They now want to move to your GoodServer and bring all their post history with them. As an admin of GoodServer, you can't see that everyone has been reporting this troll for years. They're now moving over lots of horrible, inflammatory, potentially illegal posts to your server.

In the coding index, GPT-5.5 gets 59.1, 58.5, 56.2, and 52.1 for xhigh, high, medium, and low while Muse Spark is behind at 47.5. For agentic, GPT-5.5 gets 74.1, 72.0, 69.4, and 59.7 (xhigh, high, medium, low) while Muse Spark gets 62.0 (beating only GPT-5.5 low).

GPT-5.5 only gets beaten by Opus 4.8 in their general index, is the top spot for coding, and is #3 behind Opus 4.8 and GLM-5.2 for agentic (excluding Fable 5 which takes the top spot, but is unavailable).

For me, the big thing with MiMo-V2.5-Pro and DeepSeek V4-Pro is that cached inputs are practically free. Kimi K2.7 Code is 53x more expensive for cached inputs which is 95% of my costs.

If I use 95M cached input tokens, 4M input tokens, and 1M output tokens, that'd be: $18 for cached input on Kimi K2.7 Code vs $0.34 with MiMo/DS; $3.80 for inputs on Kimi vs $1.74 with MiMo/DS; and $4 for output on Kimi vs $0.87 with MiMo/DS.

Of all the places where I'm accumulating costs by using Kimi, it's the cached inputs. The real savings with MiMo/DS's price cut is the cached inputs.

Qwen-3.6-27b is closer to Claude Opus 4.7 than it is to Haiku 4.5 in a lot of benchmarks - and it's way smaller than Microsoft's new model.

Sure, it competes with Haiku, but it shows how far Microsoft is behind lots of other small models that are available.

Yes, being exploited will leave you in a bad state, but it's also important to learn why other similarly colonized countries have done a lot better over the past 30 years - what are the conditions and policies that improve things

With egui, it's an immediate mode GUI rather than retained mode and that has trade-offs: https://github.com/emilk/egui#why-immediate-mode. It's going to use more CPU (and battery power), there can be jitter and things shifting after the initial rendering, and other stuff. I think egui is very different from most cross-platform and platform-specific libraries.

With .NET MAUI, you're getting native controls, but you're now using a layer that's trying to use native controls on the underlying systems that don't always align completely. A lot of things act mostly the same across systems, but some things don't totally.

With Flutter, your app is going to be larger in part because you're shipping a rendering engine, runtime, widgets, etc. Does it have the look and feel you want? Maybe. That's a bit subjective. Does it handle all the little things correctly? When I'm using an app, I want it to scroll like how I'm used to scrolling working on my system. If you have differently styled buttons, I don't care, but if the scrolling feels wrong, it's going to annoy me. And there's so many little things.

Frankly, one of the reasons why Electron often does well is that a lot of the little things "feel right" because the UI is essentially a Chromium-rendered web page which users are used to interacting with. But that has downsides too - shipping a web browser with your app and the memory usage.

Heck, Qt apps in Gnome or GTK+ apps in KDE can look/feel "off".

And it'll all depend on your ecosystem. Often cross-platform solutions are lacking in accessibility - sometimes completely missing, sometimes half-baked and it works in some parts and not in others or just is janky. Memory usage is often higher. Many little things that make an app feel right might not be there. Many have slower startup times since they're loading a bunch of stuff that native apps don't need to. And it really depends on what approach the cross-platform library is taking to determine what is going to cause pain.

So you kinda have to pick your poison and what's acceptable to you will vary depending on your goals and tastes. Maybe React Native is the way to go for you with lots of native controls available and the feel that provides and the performance and size is acceptable.

If you create a Flutter or Kotlin Compose Multiplatform or AvaloniaUI app and put it on the web, it's not going to feel right as something like HN does. Right-click, text selection, etc. are all going to be different or missing. If you're creating a solitaire game, maybe that doesn't matter - you get desktop and web in one go and it's not a big deal.

But you have to know what you're building to know if the trade-offs being made are good ones. This isn't meant to sound anti-cross-platform, but as someone who has suffered some pain in this area, I guess I just wanted to impart that it isn't all sunshine and rainbows. Some times it can still be worth it, but just go in with your eyes open.

Generally speaking, it's more efficient to power a car using a series-parallel hybrid system than an electric drivetrain with generator (series hybrid) while not really being any more complicated.

In a series hybrid (electric with generator), you're losing energy converting the rotational energy into electric energy. It's better to use the engine's output to power the wheels while it's in an efficient range. It's why Toyota's series-parallel hybrid design offered better mileage than vehicles that (primarily or fully) operated as series hybrids like the Chevy Volt.

> No screens

You can't really sell a car without a screen due to government regulations which require backup cameras (since 2018 in North America, since 2022 in the EU and Japan).

> no assists

Automatic Emergency Braking is going to be required in the US in 2029 (detecting frontal crashes about to happen and automatically braking, including pedestrian detection).

The EU requires even more including blind spot detection and lane-keeping assist.

I certainly agree that cars need knobs and buttons for controls like AC/heat, music, etc. However, it'd be hard to make a car where you aren't putting in a screen and assistive technology. I think a better argument would be to make a car where the screen was simply Apple CarPlay/Android Auto and a backup camera - rather than shoving a lot of garbage UX into it.

But the big reason x64 couldn't keep up was that Intel's fab capabilities were horrible. Intel got stuck and couldn't get smaller nodes out and competing fabs caught up and left Intel in the dust.

Apple was able to ship 22nm Intel processors in Summer 2012 while their iPhone processors were 32nm that Fall and 28nm in Fall 2013. Spring 2015, Apple shipped 14nm Intel laptops and later that Fall 14/16nm iPhones. Competitors had caught up and soon TSMC started surpassing Intel.

Yes, Intel's fab capabilities have improved lately, but Intel's fab failures were causing x64 to fall behind. If Intel had retained fab supremacy, x64 wouldn't have fallen behind. I think Apple still likes the idea of being able to build exactly the parts they want (so they can optimize for power, thermals, etc), but Intel fell behind because their fabs stopped being competitive.

Is there a leaderboard out there comparing harness results using the same models?

I think the issue is that it's not just bad actors. It's every social platform that strips out metadata. If I post an image on Instagram, Facebook, or anywhere else, they're going to strip the metadata for my privacy. Sometimes the exif data has geo coordinates. Other times it's less private data like the file name, file create/access/modification times, and the kind of device it was taken on (like iPhone 16 Pro Max).

Usually, they strip out everything and that's likely to include C2PA unless they start whitelisting that to be kept or even using it to flag images on their site as AI.

But for now, it's not just bad actors stripping out metadata. It's most sites that images are posted on.

It's kinda like how IBM didn't see the value in software and that let Microsoft become Microsoft.