291–300 of 400 posts
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You give it command line access in a VM...
You mean a VM like the one that contains a 0day that can escape the sandbox that gets found every year at pwn2own?
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For serious work, the difference between spending $10/month and $100/month is not even worth considering for most professional developers. There are exceptions like students and people in very low income countries, but I’m always confused by developers with in careers where six figure salaries are normal who are going cheap on tools. I find even the SOTA models to be far away from trustworthy for anything beyond thro…
You don't magically get better results by spending 10x more on a model. If your prompt is crap and harness is crap, you get crap results, regardless of model. And if you run into limits, you aren't working at all. Buying the most expensive circular saw doesn't get you the best woodworking, but it is the most expensive woodworking.
Ok I find it funny that people compare models and are like, opus 4.7 is SOTA and is much better etc, but I have used glm 5.1 (I assume this comes form them training on both opus and codex) for things opus couldn't do and have seen it make better code, haven't tried the qwen max series but I have seen the local 122b model do smarter more correct things based on docs than opus so yes benchmarks are one thing but realit…
I have been using GLM-5.1 with pi.dev through Ollama Cloud for my personal projects and I am very happy with this setup. I use pi.dev with Claude Sonnet/Opus 4.6 at work. Claude Code is great but the latest update has me compacting so much more frequently I could not stand it. I don't miss MCP tool calling when I am using pi.dev; it uses APIs just fine. I actually think GML-5.1 builds better websites than Claude Opus…
I've been using Claude Code regularly at work for several months, and I successfully used it for a small personal project (a website) not long ago. Last weekend, I explored self-hosting for the first time. Does anyone have a similar experience of having thoroughly used CC/Codex/whatever and also have an analogous self-hosted setup that they're somewhat happy with? I'm struggling a bit. I have 32GB of DDR5 (seems inad…
Grab a recent win-vulkan-x64 build of llama.cpp here: https://github.com/ggml-org/llama.cpp/releases - llama.cpp is the engine used by Ollama and common wisdom is to just use it directly. You can try CUDA as well for a speedup but in my experience Vulkan is most likely to "just work" and is not too far behind in speed.
For best quality, download the biggest version of Qwen 3.5 27B you can fit on your 4090 while still leaving room for context and overhead: https://huggingface.co/unsloth/Qwen3.5-27B-GGUF - I would try the UD-Q5_K_XL but you might have to drop down to Q5_K_S. For best speed, you could use Qwen 3.6 35B-A3B (bigger model but fewer parameters are active per token): https://huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF - probably the UD-Q4_K_S for this one.
Now you need to make sure the whole model is fitting in VRAM on the 4090 - if anything gets offloaded to system memory it's going to slow way down. You'll want to read the docs here: https://github.com/ggml-org/llama.cpp/tree/master/tools/serv... (and probably random github issues and posts on r/localllama as well), but to get started:
llama-server -m /path/to/above/model/here.gguf --no-mmap --fit on --fit-ctx 20000 --parallel 1
Go to the printed link (localhost:8080 by default) and check that the model seems to be working normally in the default chat interface. Then, you're going to want more context space than 20k tokens, so look at your available VRAM (I think the regular Windows task manager resource monitor will show this) and incrementally increase the fit-ctx target until it's almost full. 100k context is enough for basic coding, but more like 200k would be better. Qwen's max native context length is 262,144. If you want to push this to the limit you can use `--fit-target ` to reduce the free VRAM target to less than the default 1024 - this may slow down the rest of your system though.
Finally, start hooking up coding harnesses (llama-server is providing an OpenAI-compatible API at localhost:8080/v1/ with no password/token). Opencode seems to work pretty reliably, although there's been some controversy about telemetry and such. Zed has a nice GUI but Qwen sometimes has trouble with its tools. Frankly I haven't found an open harness I'm really happy with.
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GLM 5.1 was the model that made me feel like the Chinese models had truly caught up. I cancelled my Claude Max subscription and genuinely have not missed it at all. Some people seem to agree and some don't, but I think that indicates we're just down to your specific domain and usage patterns rather than the SOTA models being objectively better like they clearly used to be.
It seems like people can't even agree which SOTA model is best at any given moment anymore, so yeah I think it's just subjective at this point.
People judge models on their outputs, but how you like to prompt has a tremendous impact on those outputs and explains why people have wildly different experiences with the same model.
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GLM 5.1 was the model that made me feel like the Chinese models had truly caught up. I cancelled my Claude Max subscription and genuinely have not missed it at all. Some people seem to agree and some don't, but I think that indicates we're just down to your specific domain and usage patterns rather than the SOTA models being objectively better like they clearly used to be.
The value in Claude Code is its harness. I've tried the desktop app and found it was absolutely terrible in comparison. Like, the very nature of it being a separate codebase is already enough to completely throw off its performance compared to the CLI. Nuts.
If this was the case then Anthropic would be in a very bad spot.
It's not, which is why people got so mad about being forced to use it rather than better third party harnesses.
Pi is better than CC as a harness in almost every respect.
The way to develop in this space seems to be to give away free stuff, get your name out there, then make everything proprietary. I hope they still continue releasing open weights. The day no one releases open weights is a sad day for humanity. Normal people won’t own their own compute if that ever happens.
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For serious work, the difference between spending $10/month and $100/month is not even worth considering for most professional developers. There are exceptions like students and people in very low income countries, but I’m always confused by developers with in careers where six figure salaries are normal who are going cheap on tools. I find even the SOTA models to be far away from trustworthy for anything beyond thro…
$100 / month will get you rate limited to much to rely on with the Claude plans. People still report getting rate limited on the $200 / plan. Also not everyone wants to use Claude Code, so if they're paying API pricing it's more likely thousands of dollars a month. If you can get the same results by spending a fraction of that, why wouldn't you?
That was the breaking point, I cancelled my subscription.
As it happens I had a low coding workload over the past two weeks so I've been noodling around in PI mostly with Gemini Flash api. I like it - I even agree it's a much better harness than CC. However, the lock in is real. Even without switching models which each have their own quirks, I expect my work speed to drop drastically for at least a week or two even if I was focused on it fully. But after the learning period I think pi will be faster. The danger of course is that CC is fairly on rails while with PI you could end up spending all your time tinkering with the harness.