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Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
171–180 of 620 posts
Re: Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
#172No, but I use GLM5.1 instead of Claude/GPT.
Re: Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
#173I have! I care about data privacy and LLMs being free. I'm using the Pi coding harness but containerized and sandboxed, to make sure it's running completely offline. On my Mac Studio with 128GB RAM (or MacBook with 36GB RAM) I'm using Qwen3.6 35b, with only 3b active parameters so that it runs really fast. I've done a complete redesign for my website's homepage and blog with Django + Wagtail. The latter is interestin…
This is very similar to my setup. Pi in a container (I do let it have network access, just no access to creds or anything, only the one directory that I'm working on at the time and my ~/.pi directory), talking to llama.cpp in another container. I'm on a Strix Halo 128 GiB unified memory laptop. I've never used the frontier models in earnest, I don't believe in using proprietary tools for my programming, so I can't r…
Hopefully this isn't off-topic, but your setup sounds just like mine, Strix Halo and (I'm assuming) llama.cpp on ROCm, and I'm finding that the Qwen hybrid models don't handle prompt caching and instead re-process the context in full on every turn. I'm wondering if you were able to solve this and how?
Re: Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
#174i used to mix remote and local minimax 2.7(q3) on my strix halo, it run at 30 tg and 220 tokens pp... it was a bit painful slow, but it was a good feeling i could stay offline. unfortunately m3 which is at opus .8 levels is 460b parameters and doesn't even fit in 128gb of memory, let alone a big context. strix halo feels like a toy for ai purposes. https://kyuz0.github.io/amd-strix-halo-toolboxes/
My strix halo board is feeling more useful and less toylike with the recent performance gains combined from MTP, better quantization, and generalized performance improvements across the stack. For example, I can run Unsloth's Gemma4-31B 4-bit QAT model with around 30tg and 200pp. I don't find that to be too slow at all. Particularly because it's nearly full accuracy and good enough for a lot of different stuff I thro…
you can absolutely use it for some workloads, but as soon as you have some extra complexity for a big repo it'll take forever and the economics are so silly to the point that the electricity bill would be comparable to a subscription. I love having the possibility of running things locally if some random dude decide to pull them plug, and give me solice the fact that i can have 100% private inference, but as the main driver during the day? shoot me
Re: Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
#175Earlier quoted context omitted.
2x RTX3090 is extremely overkill for gaming, you can run any released game on earth on ultra for much less
what?
AFAIK nvidia cards dont work in tandem (aka sli in the past) very well these days. So that aint true.
Also, 2 gens old means bad performance at ray tracing, abysmal path tracing if at all. Pretty sure it can't run smoothly CP2077 in native 4k without dlss upscalers with all on ultra.
Re: Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
#176I'm using 4x RTX 5070's and first-gen AMD threadripper (1950X) to run Qwen3.6 27B (MTP) Q6_K with llama.cpp and it works great as a daily driver with Pi. Around 50-60 toks/sec. I also connect a few other applications to it such as OpenWeb UI and recently set up Bifrost, an LLM gateway, to be the primary access point for the models I serve.
I've tried other models such as Qwen3.6 35B A3B and I've found that 27B works better for me when it comes to coding. It's slower being a dense model but the quality seems much better. Inference on my system for Qwen3.6 35B A3B is around 130-140 toks/sec, non-MTP, which is insanely fast!
You don't need 4x 5070's to run Qwen3.6 27B, three or maybe even two will work. However, I use MTP (multi-token prediction) to speed up 27B and that eats up more memory because the draft model requires its own context.
Another thing to keep in mind is that the tools you're using have their system prompts that are loaded into the model for each conversation. When I fire up Pi, working with the model is very snappy at start. When I interact with the LLM via Hermes CLI, it's much slower. That's because each prompt with Hermes is loading so much stuff (skills, tools, etc.) into the context and then it's there forever until the conversation ends.
I like running models at home for privacy, but I also like how there are no quotas, usage isn't a worry. If the future is "loop engineering" then you will be burning through tokens and $$$ using a cloud models.
My system idles around 200W and is around 350-450W when inference load is high. Decoding (token generation) isn't all that efficient, and your GPUs sit idle more than you think during inference. Advancements like diffusion may 1) speed up decoding and 2) let you utilize more of your idle GPU.
Re: Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
#177I have! I care about data privacy and LLMs being free. I'm using the Pi coding harness but containerized and sandboxed, to make sure it's running completely offline. On my Mac Studio with 128GB RAM (or MacBook with 36GB RAM) I'm using Qwen3.6 35b, with only 3b active parameters so that it runs really fast. I've done a complete redesign for my website's homepage and blog with Django + Wagtail. The latter is interestin…
Given your knowledge on this - do you think we'll see an open source model with Opus levels of capability? IMO if/when this happens - I would 100% stop using Anthropic.
Let me put it like this. I started with local LLMs when ChatGPT still used GPT-3.5. I was amazed how my MacBook with 8GB RAM could run openhermes2.5-mistral: a 7b parameter model that could generate short stories that sort of made sense. Incredible!
Two years later, and I'm running Qwen3.6 35b agentically to develop the start of a repository and automatically run tests to then improve on itself. I never thought we'd get here so quickly with LLMs back then.
I'm pretty sure in two years we'll have current Opus-like quality in the 30-100b parameter model range. But at that point, Opus 6.3 will reason along for us so much better still, that we'll still look at those models in awe. It's great to look ahead, but let's not forget to appreciate how effective the current local models already are :)
Re: Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
#178I would like to say I run 100% local, but I use Opus + Gemini Pro cumulatively for 3 or 4 hours a week. I also like to use DeepSeek v4 flash with OpenCode for small quick tasks.
I did just publish a free to read online book "The Rise of Local Coding Agents" [1] where I document my setup that I enjoy using. I use little-coder (built on pi) and have good results for small Python and TypeScript applications. I struggle getting good results with Common Lisp and Clojure.
For me, the problem with all local LLM-basic coding agents is slow runtime.
Re: Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
#179I have! I care about data privacy and LLMs being free. I'm using the Pi coding harness but containerized and sandboxed, to make sure it's running completely offline. On my Mac Studio with 128GB RAM (or MacBook with 36GB RAM) I'm using Qwen3.6 35b, with only 3b active parameters so that it runs really fast. I've done a complete redesign for my website's homepage and blog with Django + Wagtail. The latter is interestin…
Given your knowledge on this - do you think we'll see an open source model with Opus levels of capability? IMO if/when this happens - I would 100% stop using Anthropic.
If you believe the benchmarks, Qwen 3.6 35B-A3B already outperforms Claude 4 Opus.
Now, there's a bit of a degree to which some of the open source models do some benchmaxxing, and bigger models with more params may always feel like they have more depth. But anyhow, right now you have something that is arguably comparable to Claude 4 Opus on your laptop. I can't really compare myself because I never used it. It looks like Claude 4 Opus is still available on OpenRouter, so you could try it out and compare yourself if you're interested.
It will likely always be the case that there are proprietary cloud models that are more powerful than what you can run on a laptop. You can just do a whole lot more with terabytes of VRAM on multi-GPU clusters than you can do on a laptop. So for folks who must have the most capable, you're probably not going to want to leave Anthropic.
But right now, the models you can run on your laptop are comparable to the cloud models that were popular when vibecoding and Claude Code first took off.
Re: Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?
#180Not 100%, I still fall back to Claude for most day-job stuff. But I've been trying to use Qwen 3.6 and Gemma 4 on my framework desktop mainboard (Strix Halo) as much as possible.
I've been working on an ops style tool for local LLM inference. Proxying, api keys, request logging, model rewriting and much much more.