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  desk setup thread for Gemma
Posted by: bytegarden73 - 10-03-2026, 04:35 PM - Forum: Off Topic - Replies (13)

Spent some time on this today and wanted to compare notes.

I'm comparing two approaches here: keep it simple on 4090, or squeeze more out of the stack and deal with the complexity.

Trying to avoid rebuilding the whole thing twice.

I care more about stability than squeezing the last possible tokens/sec out of it.

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  QLoRA resource reality check
Posted by: cacheline - 10-03-2026, 04:04 PM - Forum: Benchmarks - Replies (14)

Spent some time on this today and wanted to compare notes.

I've gone back and forth between llama.cpp and MLX for FLUX. The interesting difference for me has been small local stacks.

Interested in tradeoffs more than fan loyalty.

This is mostly for local work rather than public serving.

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  Help with Search / Retrieval / Reranking
Posted by: thetarunner - 10-03-2026, 03:52 PM - Forum: Search / Retrieval / Reranking - Replies (2)

Thought I'd post a small recipe because a lot of threads ask similar things.

Just sharing a setup that ended up working reasonably well: Gemma, TensorRT-LLM, M3 Max, with a lot of attention on consumer GPUs.

Maybe useful as a starting point for newer folks.

If I had to summarize the lesson so far, it would be that clean setup and observability beat clever guesses.

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  vector DB that stayed out of the way
Posted by: quantyard - 10-03-2026, 03:23 PM - Forum: Model Merging - Replies (11)

Posting this in case it saves someone else a little time.

I'm helping a small team set up a local workflow. We don't need a giant stack, but we do care about structured output.

Would rather learn from your scars than collect my own all at once.

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  good hosted AI app that still respects privacy for Mistral
Posted by: mangopath4 - 10-03-2026, 01:46 PM - Forum: Online / Hosted - Replies (15)

This keeps coming up in conversation so I figured I'd start a thread.

One thing I keep noticing is that people underestimate prefix caching until they actually try to run this stuff for more than one afternoon.

Curious whether that lines up with what other people are seeing.

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  VRAM saving for image generation for Gemma
Posted by: mangopeak72 - 10-03-2026, 11:54 AM - Forum: Model Comparisons - Replies (11)

Spent some time on this today and wanted to compare notes.

I'm comparing two approaches here: keep it simple on M3 Max, or squeeze more out of the stack and deal with the complexity.

Interested in tradeoffs more than fan loyalty.

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  Search / Retrieval / Reranking discussion with PyTorch
Posted by: cacheline - 10-03-2026, 10:05 AM - Forum: Search / Retrieval / Reranking - Replies (14)

Maybe I'm missing something obvious.

I'm trying to decide whether to keep the current stack or change course. Main question is how people here are handling reranking.

If you've tested something similar, what did you keep and what did you stop bothering with?

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  good hosted AI app that still respects privacy with SGLang
Posted by: torchsmith25 - 10-03-2026, 09:13 AM - Forum: Online / Hosted - Replies (9)

This keeps coming up in conversation so I figured I'd start a thread.

One thing I keep noticing is that people underestimate prefill/decode split until they actually try to run this stuff for more than one afternoon.

Wondering if this is just where the whole space is heading now.

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  HIP kernel compile issue for Llama
Posted by: thetaember38 - 10-03-2026, 06:49 AM - Forum: AMD / ROCm - Replies (1)

Posting this in case it saves someone else a little time.

I'm helping a small team set up a local workflow. We don't need a giant stack, but we do care about embeddings.

Would rather learn from your scars than collect my own all at once.

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  mobile NPU reality check
Posted by: fastquill74 - 10-03-2026, 06:28 AM - Forum: Mobile - Replies (9)

Posting this in case it saves someone else a little time.

If you were starting from scratch today for this use case, what would you choose first and what would you ignore?

Simple and boring is a valid answer.

This is mostly for local work rather than public serving.

If I had to summarize the lesson so far, it would be that clean setup and observability beat clever guesses.

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