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Seems to completely ignore usage of local/free models as well as anything but Sonnet/ChatGPT. So my confidence in the good faith of the author is... heavily restricted.
Do you use a local/ free model?
Seems to completely ignore usage of local/free models as well as anything but Sonnet/ChatGPT. So my confidence in the good faith of the author is... heavily restricted.
Most people can’t affort the GPUs for local models if you want to get close to cloud capabilities.
Seems to completely ignore usage of local/free models as well as anything but Sonnet/ChatGPT. So my confidence in the good faith of the author is... heavily restricted.
Most people can’t affort the GPUs for local models if you want to get close to cloud capabilities.
A 5090 has 32GB of VRAM allowing you to run a 32B model in memory at Q6_K.
You can run larger models by splitting the GPU layers that are run in VRAM vs stored in RAM. That is slower, but still viable.
This means that you can run the Qwen3-Coder-30B-A3B model locally on a 4090 or 5090. That model is a Mixture of Experts model with 3B active parameters, so you really only need a card with 3B of VRAM so you could run it on a 3090.
The Qwen3-Coder-480B-A35B model could also be run on a 4090 or 5090 by splitting the active 35B parameters across VRAM and RAM.
Yes, it will be slower than running it in the cloud. But you can get a long way with a high-end gaming rig.
Earlier quoted context omitted.
Do you use a local/ free model?
I am currently using a local model qwen3:8b running on a 2020 (2018 intel chip) Mac mini for classifying news headlines and it's working decently well for my task. Each headline takes about 2-3 seconds but is pretty accurate. Uses about 5.3 gigs of ram.
Earlier quoted context omitted.
Most people can’t affort the GPUs for local models if you want to get close to cloud capabilities.
A 4090 has 24GB of VRAM allowing you to run a 22B model entirely in memory at FP8 and 24B models at Q6_K (~19GB). A 5090 has 32GB of VRAM allowing you to run a 32B model in memory at Q6_K. You can run larger models by splitting the GPU layers that are run in VRAM vs stored in RAM. That is slower, but still viable. This means that you can run the Qwen3-Coder-30B-A3B model locally on a 4090 or 5090. That model is a Mix…
Earlier quoted context omitted.
Most people can’t affort the GPUs for local models if you want to get close to cloud capabilities.
A 4090 has 24GB of VRAM allowing you to run a 22B model entirely in memory at FP8 and 24B models at Q6_K (~19GB). A 5090 has 32GB of VRAM allowing you to run a 32B model in memory at Q6_K. You can run larger models by splitting the GPU layers that are run in VRAM vs stored in RAM. That is slower, but still viable. This means that you can run the Qwen3-Coder-30B-A3B model locally on a 4090 or 5090. That model is a Mix…
> The Qwen3-Coder-480B-A35B model could also be run on a 4090 or 5090 by splitting the active 35B parameters across VRAM and RAM.
Reminds me of running Doom when I had to hack config.sys to forage 640KB of memory.
Less than 0.1% of the people reading this are doing that. Me, I gave $20 to some cloud service and I can do whatever the hell I want from this M1 MBA in a hotel room in Japan.
For development use cases, I switched to Sonnet 4.5 and haven't looked back. I mean, sure, sometimes I also use GPT-5 (and mini) and Gemini 2.5 Pro (and Flash), and also Cerebras Code just switched to providing GLM 4.6 instead of the previous Qwen3 Coder so those as well, but in general the frontier models are pretty good for development and I wouldn't have much reason to use something like Sonnet 4 or 3.7 or whateve…
Isn’t this obvious? When you have a task you think is hard. You give it to a cleverer model. When a task is straight forward you give it to an older one.
As evidenced by furious posters on r/cursor, who make every prompt to super-opus-thinking-max+++ and are astonished when they have blown their monthly request allowance in about a day.
If I need another pair of (artificial) eyes on a difficult debugging problem, I’ll occasionally use a premium model sparingly. For chore tasks or UI layout tweaks, I’ll use something more economical (like grok-4-fast or claude-4.5-haiku - not old models but much cheaper).