| ▲ | canpan 4 hours ago |
| The nice thing is that current local modes don't go away. The weights are out. Qwen 27b and deepseek are already very useful. Hardware will keep getting stronger so after the current memory crisis you can run them more cheaply. Of course the proprietary models will continue to improve and we have no guarantee that there will be new open models. But for coding, the local models are already good enough for a vast amount of use cases, if you are an experienced developer yourself and can guide it. |
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| ▲ | pinyen_cheng 3 hours ago | parent | next [-] |
| I think the future should be efficient quantization which can make model with the same level as Qwen 3.8 27b now accessible from our laptop. |
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| ▲ | Moto7451 2 hours ago | parent [-] | | This is mostly a memory bandwidth issue. Qwen 3.8 27b and the related Bonsai 2 27B run on my M5 Max laptop with 36GB of ram. It’s a little slow due to my specific model having lower memory bandwidth than higher end models with more ram and cores. MoE models perform better here and expert streaming engines can allow larger than memory models to run. | | |
| ▲ | nout 2 hours ago | parent [-] | | Multiple teams and efforts are now making Qwen 3.8 27b work much faster on Mac and CUDA and the inference speed is doubling almost every week.
There's now ongoing competition about who will make it work faster with exactly the same byte output at https://mlx.fast . TensorFold is the project to follow. |
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| ▲ | girvo an hour ago | parent | prev | next [-] |
| Its possible (though very hard to do well, and needs a fair bit of compute) to improve the local models we have, too. Continued training is possible as time goes on. |
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| ▲ | Havoc 4 hours ago | parent | prev | next [-] |
| >The nice thing is that current local modes don't go away. Given pace of advance I'm not convinced this is a winning strategy. The models of today (open or not) are way smarter than those of a year ago. ...so we really do need open models to keep pace, not just be statically competitive at a given point in time |
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| ▲ | ashkankiani 4 hours ago | parent [-] | | Even if Deepseek v4.1 is the last open source LLM I have access to, I would be perfectly fine with that. My secret is that I have this relatively unknown technique for solving problems where I use this quantum engine that developed from just atoms over 4.54 billion years into the most sophisticated machine in the known universe. It's a frontier model that every human has access too, actually. So when I really want to solve a problem, I just think on it. And when I need something to iterate through the things I thought of quickly, I use deepseek. | | |
| ▲ | cortesoft 35 minutes ago | parent | next [-] | | You say that now, but you don't know what the future models will be capable of. If models get ridiculously good, you might not be perfectly fine with that. | | | |
| ▲ | edot 4 hours ago | parent | prev | next [-] | | Yep, fully satisfied with DS 4.1 Flash or GLM 5.3 Flash. I prefer using one chat at a time, actually thinking through things with it, as opposed to the YOLO run all night multi-agent thing. I mean I’m still okay with subagents if my main thread needs to explore a few options and then report back, but all on the same idea. | |
| ▲ | SequoiaHope 2 hours ago | parent | prev | next [-] | | The thing here for me is not that I’m unable to solve problems with my brain, it’s that I value the automation in labor provided by coding agents. I do not want future advancements to be locked behind proprietary doors. | | |
| ▲ | ashkankiani an hour ago | parent [-] | | I agree with that but the cat is out of the bag now. Unless you believe in exponential improvement (which I don’t), the open models might be at a resource disadvantage, but that doesn’t mean that they can’t catch up or surpass the closed ones. Throwing money at a problem doesn’t guarantee success. I mainly just want to point out the value of human ingenuity coupled with a model like DS4.1 is technically enough to get most people to where they want to go, and that includes smarter open models. |
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| ▲ | Obscurity4340 4 hours ago | parent | prev | next [-] | | How do you run DS 4.1 Flash if your computer isnt powerful and everything? | | |
| ▲ | ashkankiani 3 hours ago | parent [-] | | It can run on one strix halo machine, which is what I have. For everything else, there’s a vibrant community brute forcing more efficient engines and quantizations. There’s a minimum bar right now, so it depends on your hardware. | | |
| ▲ | fooblaster 3 hours ago | parent [-] | | you have 5k$ of ram in a strix halo? | | |
| ▲ | ashkankiani 3 hours ago | parent [-] | | I bought my box for $3k last year because I hadn't updated my PC since the first threadripper 1950x, and the Strix Halo is the only x86 with unified memory that's optimized for the kind of CPU intensive stuff I do, and they finally have proper AVX512 too. It was the perfect upgrade for me (except for lack of PCIe 5 & ECC), which coincidentally happened to be perfectly positioned for local inferrence. and I liked it so much (and saw that the RAM drought was going to last for at least a few years) so I bought a second one to use as a general server for myself and my family. |
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| ▲ | Havoc 4 hours ago | parent | prev [-] | | The fact that you point to the latest model as „I’d be fine with that“ proves my point. If expectations were static you’d be fine with qwen 2.5…but nobody sane says that today. It’s a moving target thus we need open weights to move | | |
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| ▲ | avazhi 2 hours ago | parent | prev [-] |
| I’m all for local models and getting away from Anthropic/OAI but Qwen 27B might as well be a horse drawn carriage compared to a 2026 Porsche. Like, I guess it’s useful if you had nothing better but acting like it’s comparable to anything the frontier models have is just disingenuous. |
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| ▲ | jeffyaw 2 hours ago | parent [-] | | disagree, it’s absolutely comparable. but an m5 max is where it shines. and there are 50 flags to finetune with llama server before you get it right. i do prefer llama server over mlx currently on mac as well. | | |
| ▲ | dontlaugh 2 hours ago | parent [-] | | It’s so poor for most tasks that you’re faster doing it manually. DeepSeek and GLM are useful, though. Even the flash variants. | | |
| ▲ | jacquesm 43 minutes ago | parent [-] | | I have all three and you're not going to convince me of that. Side-by-side Qwen 3.8 27B is ~6x as fast as DS4 and GLM 5.3 and faster than that if you get the speculative engine set up properly. That means you can iterate very rapidly on the same problem and for many problems this is the way to solve them. DS4 and GLM 5.3 shine when Qwen would take too many turns to solve something, they simply have more world knowledge and seem to home in on possible solutions faster in #tg but slower in wall clock time. If a particular problem is within striking range of all three then Qwen will usually be the fastest solver by far. It also depends on how good your prompt is, whether you are setting up points for guidance or whether you expect everything to be solved in a single shot. |
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