131–140 of 620 posts
Like "Here's this consumer grade GPU. Using only this GPU but with whatever models and workflow you want, see how well you can do on xyz benchmark."
Contestants would be given like 1 hour max and scored based on % of questions answered, % of questions correct and total time to finish.
Like "The Local AI challenge"
Always a bit disappointed in the details in these kinds of threads. When you do get answers, they're never specific enough to try out on your own. It'll be something like "I use Qwen 3.5 and get great results!" OK but what quantization are you using? What llama parameters? What context size? What GPU are you running it on, and how much VRAM does it have? Are you hosting it on a separate box, or running it locally on…
I have good results with this setup: Hardware: - GPU: AMD 7900xtx, 24gb vram - CPU: AMD 5950x, AM4 - RAM: 64gb DDR4 3600 Software: - OS: Bazzite (atomic fedora - this machine is running Steam "big picture" mode on my TV when not in use for LLM tasks) - Virtualization: Podman Quadlets, which allows me to run container images as managed systemd units - Network: tailscale - Inference: llama.cpp vulkan (better performanc…
For personal use, yes. I replaced a $100/m subscription to claude in favor of running pi harness pointed at unsloth studio, using both qwen (unsloth/Qwen3.6-35B-A3B-MTP-GGUF) and gemma (unsloth/gemma-4-26B-A4B-it-GGUF) models, depending on my mood. I have a machine I built about 5 years ago with dual RTX3090s in it (I was going to build a new gaming machine anyways, and the llama release had just dropped so I tacked…
Since you're running quantized (at UD-Q4_K_XL) , check out the "qat" models (unsloth/gemma-4-26B-A4B-it-qat-GGUF) !
- https://huggingface.co/unsloth/gemma-4-26B-A4B-it-qat-GGUF (With "Jun 9 Update: Added MTP support.")
- https://blog.google/innovation-and-ai/technology/developers-...
but then use cheap/local model to implement the specs.
Markdown is more effective at compressing information and fits the context window easier, than hundreds of source code files
but this requires second and third passes, to smooth out the rough edges
has anyone tried that?
Models that you can run at home (Like Qwen 35B) aren't remotely close to Opus or GPT 5.5. Not even close. The only open models that are in that neighbor are around 1T params, so forget about running at home. It's kind of like driving a shitbox. It can often drive you from A to B, and some people will try to convince you it's fine. It's not. There's no logical reason other than absolutely requiring the privacy, doing…
Is that characterization based on some objective facts or benchmarks?
I 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…
Could the harness not check for a failed tool call and pass it to a small model for correction without clogging up the main context?
I'll experiment more with the effectiveness of AGENTS.md rules for local Pi agents. I feel like smaller (local) LLMs just lack in attentiveness to elements in the context window, like precise instructions, compared to e.g. Claude models.
I mostly use it as a google search if I forget a thing, or doing the boilerplates.
I am using a mix of a non harness chat for the reply speed, and opencode / vim-ai for my boilerplates.
$0.00 / month. That's the budget.
I 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…
For personal use, yes. I replaced a $100/m subscription to claude in favor of running pi harness pointed at unsloth studio, using both qwen (unsloth/Qwen3.6-35B-A3B-MTP-GGUF) and gemma (unsloth/gemma-4-26B-A4B-it-GGUF) models, depending on my mood. I have a machine I built about 5 years ago with dual RTX3090s in it (I was going to build a new gaming machine anyways, and the llama release had just dropped so I tacked…
2x RTX3090 are around $4400. Without any electricity costs or other parts, that's 3.6 years of $100/m claude.