HN rank: 1

HN score: 730

comments: 279

original url: https://openrouter.ai/deepseek/deepseek-v4-pro-0813

评论信号：Why does this link to OpenRouter, which has no useful information on its own? Linking to the official API or the benchmarks would make more sense:- https://api-docs.deepseek.com/- https://x.com/ChrisGPT/status/2087572834650407024/photo/1 (officially posted on WeChat, this is just one of many reposts) reply: There's no new page for this model. Hackernews didn't allow the same link be posted twice.

评论信号：Have been letting it spin pretty hard (~$12.50 for 2B, 50% cache hits) on my traffic simulator/distributed physics engine all day, it's found some pretty significant gains without introducing any new problems.I'm happy reply: 50% cache hit is really low - in a standard agentic loop you should expect like 99%+ cache hit percentage (which should also lower that $12.50 to like a couple of $ for the same amount of tokens).If you're using a customised harness you should make sure you don't have something that's e.g. changing your system prompt on some requests or rewriting history - it can be tempting to do stuff like strip old thinking tokens or compact tool call results to reduce context size but it's a trap - you want to never change history because of how cheap cache is, even more so with deepseek because their cache hit pricing is so low compared to most other models.

评论信号：Nice bicycle chain, the little basket with a fish didn't show up in the right place: https://tools.simonwillison.net/markdown-svg-renderer#url=ht... reply: On either side of the front wheel is a perfectly reasonable place to carry cargo. I think I'd have taken more issue with the spokes, or at least that's what stood out to me. The chain is indeed nice, however.

HN rank: 2

HN score: 383

comments: 127

original url: https://zed.dev/blog/introducing-delta

评论信号：I think Zed is an excellent editor (fast!) with a pretty good AI agent built-in, but I have no desire to do multi-player development in my editor. Never have had any such desire. Coding is a single-player game and I can't think of a single thing that would be improved by having someone else in the same editor.So, this seems like a lot of work on really cool tech for no useful purpose at all?Are there people crying out for a multi-user code editor? I mean, we have to have code reviews, sure. That involves other people or other agents. But, I don't need to stand over someone's shoulder while they work. That seems like the worst thing in the world for everyone involved. I don't want an audience for my dumb looking experiments because I forgot how to do something. reply: Pair programming is a great way to do knowledge sharing and collaborate on tricky problems. Now, I don't really want a multiplayer editor, but I'll highly contest that coding is solely a solo activity.Sometimes I feel like people online hate all their coworkers. Thankfully, such people have not been highly represented amonst those I've worked with.

评论信号：Does anyone else hate reading AI summaries of code? Code can be pithy, but at least its terse compared to prose. When you add how verbose LLMs can be, I often end up reading a paragraph to explain a few lines. Or the opposite happens where the summary skips important edge cases or criteria. "You're right, X also does Y. I missed that in my initial analysis," is much too common of a phrase.I like the idea of using LLMs to transform code into something more readable, and vice versa. I am not sure if meandering paragraphs and linear lists are the best targets. reply: I wonder if a productive avenue might be "doing aspect-oriented programming in reverse": asking the LLM not to "summarize" the code per se, but rather to "clarify" it by transforming it into what a programming blog post would call a "toy example" of what the code is doing, by stripping out all the (non-semantic) error-handling, logging, metrics incrementing, etc — all the things that you might treat as their own "aspects" under AOP.

评论信号：This is intriguing. The two relevant features seem to be 1) realtime collaborative multiplayer conversations and 2) conversation-as-document - basically, letting you comment inline in an agent conversation.For (1), the main value I'd see is in mentoring junior engineers or less technical contributors on a team. If someone puts up a PR with sloppy results, you could actually jump into the thread that produced that PR and see how the results came about, or even coach that contributor on how to do better next time. Also might make it easier to hand off work from one person to another - right now most coding agent sessions are user-local.On (2), I frequently find myself consuming agents' gigantic text responses and tediously writing 8-bullet-point responses to guide them. It's pretty exhausting. I could see inline comments providing much better ergonomics.All that being said, Zed has largely fallen out of the conversation for "agentic coding tools", and so this feels like their attempt at creating something like the Cursor Agents Window, Codex, or Claude Code. These two features seem compelling, and I understand they're even compatible with other coding harnesses.... reply:...

HN rank: 3

HN score: 790

comments: 141

original url: https://tailscale.com/blog/sqlite-wal-reset-bug

评论信号：> We funded the open-source SQLite VFS shim that helped isolate the race condition almost immediately, and will help track down similar bugs in the future.Interesting example of a company funding open source - in this case paying for the development of a new and very specific debugging tool. reply: Not only are they funding open source, they are actively allowing users to host their own control plane via headscale which is a libre implementation of the tailscale control protocol and developed by an engineer who works for Tailscale by day. This instantly made me trust and like them, even if at first I was cautious because I naturally mistrust anything that gets a lot of hype. I've been running headscale on NixOS, hosting my own tailnet since last year and everything just works out of the box. Tailscale lives up to the hype! <3

评论信号：Well written post, really enjoyed reading it.> A single Go process exclusively accesses that database, and serves the control plane for those tailnets. This single-writer design is exactly how SQLite is meant to be used.This line led me to believe that the writer and checkpointing logic lived on the same database connection, so I was curious to find out how the data race occurred. However, the bug details on the SQLite page[0] outline that it can only ever occur if there are multiple connections open, so the writer and the checkpointer must have been on different threads.[0] https://sqlite.org/wal.html#the_wal_reset_bug

评论信号：SQLite: 92 million lines of testsDijkstra: Tests can only prove the presence of bugs, never their absence! reply: Everyone knows that tests don't prevent all bugs. But they are very good at preventing known bugs from recurring in the future.

HN rank: 4

HN score: 22

comments: 3

original url: https://sharktastica.co.uk/articles/pc-fxt-45

评论信号：time to boot up some Lode Runner.

评论信号：I wonder what the average CS grad thinks of these days when they hear the company name "IBM".

评论信号：Apple II home computers and TRS-80 are 48.

HN rank: 5

HN score: 487

comments: 105

original url: https://huggingface.co/Qwen/Qwen3.8-2.4T-A95B

评论信号：Supposedly this is a Kimi k3 rival. Bit of a chonker, especially since they only released bf16 and fp8. So at launch this will be harder to serve than k3. No QAT on q4 means that someone with deep pockets (nvda?) will have to quant it, with plenty of calibration data. Should bring it ~1.3TB, so around k3 size.License pretty similar to k3 with some caveats. Free to use for internal or 3.8-max shows a lot of improvement. reply: The parameter "reasoning_effort" is something new, or am I wrong? Qwen3.8 comes with official support for reasoning_effort, which can be used to adjust reasoning depth and control cost:

• xhigh (default): for complex tasks demanding thorough analysis
• medium: balancing accuracy and speed
• low: efficient reasoning optimizing for speed and cost In addition, preserve_thinking is enabled by default for all workloads for the best out-of-the-box experience.

Asking because in my case (OCR of scanned historical "National Geographic" magazines) the LLM trying to merge text split into separate columns was running in circles from time to time and needed a lot of prompt tuning when using Qwen 3.0/3.5/3.6 (still needs from time to time).

评论信号：Also of interest: DeepSeek V4-Pro-0813 (1.6T-A49B) benchmark scores have apparently just been announced on the DeepSeek WeChat channel and they're sitting about Fable 5 level.[1][1] https://www.reddit.com/r/LocalLLaMA/comments/1vmi0fg/deepsee... reply: Isn't this quite a bit behind Sol and Fable and even ChatGPT 5.5 xhigh and Opus 5 max?In terms of what you get for what you pay for, it's incredible - probably by far the best.But unless I'm reading things wrong, it does not appear to be top-of-the-line.

评论信号：https://unsloth.ai/docs/models/qwen3.8The 1bit quant model is at an astonishing 397GB with 95B active per MOE. This literally puts Opus 4.5 performance level into a machine a normal person could buy, and still gets usable tokens/second.The full lossless model BF16 is clocking at 4.9TB. The model card claims the model to be between Opus 4.8 and Fable 5. Again that's astonishing as getting a machine with 7TB RAM (with context + KV cache) is still within the realm of medium size companies.Bad things: The open source version has its vision capability removed, and the context capped at 250k . I expect someone to bolt a Kimi 2.6 vision tower to it to restore the vision capability (at less performance of course). For context, I played around with extending the context to 600k for Qwen 3.5 397b, and the context remained stable up to around 480k. It'd be interesting to see if the same can be done to Q3.8 .Also no out of the box DSpark/DFlash support. MTP is present so we should at least get some boost in TP speed. reply: To compare a 1 bit quant to the full fat model is misleading.Honestly this model people at home can tinker with, if you have a big enough Mac....