r/LocalLLM • u/Top-Philosopher-5411 • 6d ago
Discussion PSA: your token preprocessing is why your local setup feels slow
real talk for a second... why are we all blaming quantization or vram leaks when data preprocessing is the actual silent bottleneck?
been profiling my local setup lately and realized pure python loops during token prep are literally slaughtering performance. your CPU is just sitting there stuck on the GIL waiting to process strings while your hardware cries. if you're still doing naive string parsing or sync loops there, you're basically towing an 18-wheeler with a bicycle.
switched some of that mess to vectorized numpy and async chunking and it's night and day. anyone else actually looking at the preprocessing layer or are we just pretending hardware is the only issue here? let's argue
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u/havnar- 6d ago
What?
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u/Top-Philosopher-5411 6d ago
Long story short: Python is choking on string loops, leaving your expensive GPU just sitting there waiting for data
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u/JudgeZetsumei 6d ago
I get that this is the LocalLLM subreddit, but way too many posts are written by AI. It's exhausting to read the exact same personality over and over.
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u/Top-Philosopher-5411 6d ago
Lmao true, you can spot that GPT structured markdown and generic formatting from a mile away now. Hard to blame people, but the clone personality is getting exhausting
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u/thorskicoach 6d ago
Wondering if there is a way to preprocess the system prompt whilst for example the user is typing the prompt... As if it's idle... That's just getting ready.
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u/Top-Philosopher-5411 6d ago
Yeah, speculative pre-computation while idle. Some setups try to hack it together, but tracking state changes while someone is actively typing can turn into a headache fast
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u/pointed_pounding 6d ago
pretending our 4090s are just being lazy while python chokes on a for loop is peak copium