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Help with Vector Databases for DeepSeek
#1
Curious what people here are seeing.

I'm mostly working with DeepSeek in MLX on GB200. The part I'm trying to understand is prefix caching.

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

For context, I'm not chasing leaderboard numbers. I mostly want the system to feel consistent day to day.
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#2
Good point. I ended up in about the same place using MLX. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.

I'm happy to test one more variant if you want a second data point.
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#3
I'd approach it in a boring order. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at embeddings.
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#4
A couple things I'd check first. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at NVFP4. Once you know the plain path works, then add the faster path back in piece by piece.
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#5
Ran a quick check on my box. On Threadripper box with Ollama, I saw basically the same behavior. I expected the model choice to matter more than it did.
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#6
subscribed, curious where this lands.
context windows are not a product strategy
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#7
A couple questions before I guess too hard. Are you testing this on dual 3090 or something else?
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#8
Appreciate the detail. The pattern around MoE serving has been pretty similar for me. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.
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#9
Quote:Appreciate the detail. The pattern around MoE serving has been pretty similar for me. Worth rechecking your defaults though, because one bad assumptio

following this because I'm in the same boat.
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#10
Quote:[quote]Appreciate the detail. The pattern around MoE serving has been pretty similar for me. Worth rechecking your defaults though, because one bad as

Appreciate the detail. I ended up in about the same place using LM Studio. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
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