What is this S/A/B/C/etc. ranking? Is anyone else using it?
Apparently S being a level above A comes from Japanese grading. I’ve been confused by that, too.
It's very common in Japanese-developed video games as well
Can I run AI locally?
61–70 of 382 posts
Re: Can I run AI locally?
#62This seems to be estimating based on memory bandwidth / size of model, which is a really good estimate for dense models, but MoE models like GPT-OSS-20b don't involve the entire model for every token, so they can produce more tokens/second on the same hardware. GPT-OSS-20B has 3.6B active parameters, so it should perform similarly to a 3-4B dense model, while requiring enough VRAM to fit the whole 20B model. (In term…
While your remark is valid, there's two small inaccuracies here:
> GPT-OSS-20B has 3.6B active parameters, so it should perform similarly to a 3-4B dense model, while requiring enough VRAM to fit the whole 20B model.
First, the token generation speed is going to be comparable, but not the prefil speed (context processing is going to be much slower on a big MoE than on a small dense model).
Second, without speculative decoding, it is correct to say that a small dense model and a bigger MoE with the same amount of active parameters are going to be roughly as fast. But if you use a small dense model you will see token generation performance improvements with speculative decoding (up to x3 the speed), whereas you probably won't gain much from speculative decoding on a MoE model (because two consecutive tokens won't trigger the same “experts”, so you'd need to load more weight to the compute units, using more bandwidth).
Re: Can I run AI locally?
#63Earlier quoted context omitted.
Yes. But llmfit is far more useful as it detects your system resources.
Honestly I was surprised about this. It accurately got my GPU and specs without asking for any permissions. I didnt realize I was exposing this info.
I run LibreWolf, which is configured to ask me before a site can use WebGL, which is commonly used for fingerprinting. I got the popup on this site, so I assume that's how they're doing it.
Re: Can I run AI locally?
#64If anyone hasn't tried Qwen3.5 on Apple Silicon, I highly suggest you to! Claude level performance on local hardware. If the Qwen team didn't get fired, I would be bullish on Local LLM.
Re: Can I run AI locally?
#65This seems to be estimating based on memory bandwidth / size of model, which is a really good estimate for dense models, but MoE models like GPT-OSS-20b don't involve the entire model for every token, so they can produce more tokens/second on the same hardware. GPT-OSS-20B has 3.6B active parameters, so it should perform similarly to a 3-4B dense model, while requiring enough VRAM to fit the whole 20B model. (In term…
The docs page addresses this:
> A Mixture of Experts model splits its parameters into groups called "experts." On each token, only a few experts are active — for example, Mixtral 8x7B has 46.7B total parameters but only activates ~12.9B per token. This means you get the quality of a larger model with the speed of a smaller one. The tradeoff: the full model still needs to fit in memory, even though only part of it runs at inference time.
> A dense model activates all its parameters for every token — what you see is what you get. A MoE model has more total parameters but only uses a subset per token. Dense models are simpler and more predictable in terms of memory/speed. MoE models can punch above their weight in quality but need more VRAM than their active parameter count suggests.
Re: Can I run AI locally?
#66Is there a reliable guide somewhere to setting up local AI for coding (please don’t say ‘just Google it’ - that just results in a morass of AI slop/SEO pages with out of date, non-self-consistent, incorrect or impossible instructions). I’d like to be able to use a local model (which one?) to power Copilot in vscode, and run coding agent(s) (not general purpose OpenClaw-like agents) on my M2 MacBook. I know it’ll be s…
Ollama or LM Studio are very simple to setup. You're probably not going to get anything working well as an agent on an M2 MacBook, but smaller models do surprisingly well for focused autocomplete. Maybe the Qwen3.5 9B model would run decently on your system?
Right - setting up LM studio is not hard. But how do I connect LM Studio to Copilot, or set up an agent?
Re: Can I run AI locally?
#67Raspberry pi? Say 4B with 4GB of ram. I also want to run vision like Yocto and basic LLM with TTS/STT
I've been trying to get speech to text to work with a reasonable vocabulary on pis for a while. It's tough. All the modern models just need more GPU than is available
For ASR/STT on a budget, you want https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3 - it works great on CPU.
I haven't tried on a raspberry pi, but on Intel it uses a little less than 1s of CPU time per second of audio. Using https://github.com/NVIDIA-NeMo/NeMo/blob/main/examples/asr/a... for chunked streaming inference, it takes 6 cores to process audio ~5x faster than realtime. I expect with all cores on a Pi 4 or 5, you'd probably be able to at least keep up with realtime.
(Batch inference, where you give it the whole audio file up front, is slightly more efficient, since chunked streaming inference is basically running batch inference on overlapping windows of audio.)
EDIT: there are also the multitalker-parakeet-streaming-0.6b-v1 and nemotron-speech-streaming-en-0.6b models, which have similar resource requirements but are built for true streaming inference instead of chunked inference. In my tests, these are slightly less accurate. In particular, they seem to completely omit any sentence at the beginning or end of a stream that was partially cut off.
Re: Can I run AI locally?
#68Earlier quoted context omitted.
Ollama or LM Studio are very simple to setup. You're probably not going to get anything working well as an agent on an M2 MacBook, but smaller models do surprisingly well for focused autocomplete. Maybe the Qwen3.5 9B model would run decently on your system?
Right - setting up LM studio is not hard. But how do I connect LM Studio to Copilot, or set up an agent?
Basically LM Studio has a server that serves models over HTTP (localhost). Configure/enable the server and connect OpenCode to it.
Try this article https://advanced-stack.com/fields-notes/qwen35-opencode-lm-s...
I'm looking for an alternative to OpenCode though, I can barely see the UI.
Re: Can I run AI locally?
#69Is this just llmfit but a web version of it? https://github.com/AlexsJones/llmfit
That's super handy, thanks for sharing the link. Way more useful than the web site this post is about, to be honest.
It looks like I can run more local LLMs than I thought, I'll have to give some of those a try. I have decent memory (96GB) but my M2 Max MBP is a few years old now and I figured it would be getting inadequate for the latest models. But llmfit thinks it's a really good fit for the vast majority of them. Interesting!
Re: Can I run AI locally?
#70Has anyone actually built anything with this tool?
The website says that code export is not working yet.
That’s a very strange way to advertise yourself.