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  framework overhead in real deployments: anyone testing this?
Posted by: embershed99 - 10-18-2026, 07:13 PM - Forum: PyTorch / JAX / Other Frameworks - Replies (11)

Did a small comparison this afternoon. On mini PC with TensorRT-LLM, I saw basically the same behavior. The surprise was that memory pressure showed up before throughput collapsed.

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  Tensor cores actually helping here
Posted by: thetapath - 10-18-2026, 07:02 PM - Forum: NVIDIA / CUDA - Replies (7)

worth checking the driver first.

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  70B still worth the pain
Posted by: sparrowbrook - 10-18-2026, 06:55 PM - Forum: Proprietary / Frontier - Replies (15)

Appreciate the detail. I ended up in about the same place using vLLM. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.

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  Blackwell deployment chatter
Posted by: oxidemixer - 10-18-2026, 06:50 PM - Forum: NVIDIA / CUDA - Replies (2)

I hit almost the same issue last night.

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  running local models on a phone
Posted by: fusedriver - 10-18-2026, 06:44 PM - Forum: Mobile - Replies (10)

Quote:Appreciate the detail. I don't think your conclusion is far off.

I'd approach it in a boring order. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at quant drift.

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  dual GPU split inference
Posted by: dockkite69 - 10-18-2026, 06:38 PM - Forum: GPUs - Replies (11)

Interesting, I hadn't tried that. I don't think your conclusion is far off. The biggest change for me was simplifying the stack instead of adding one more optimization layer.

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  quality tests for local assistants
Posted by: edgeriver - 10-18-2026, 06:37 PM - Forum: Evals - Replies (5)

Interesting, I hadn't tried that. I ended up in about the same place using Ollama. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.

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  DeepSeek V4.1 impressions for Llama
Posted by: rocmhouse90 - 10-18-2026, 06:25 PM - Forum: Workflows / Automation - Replies (15)

Quote:
Quote:that fixed it for me too.

Thanks, that helps. I ended up in about the same place using PyTorch. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.

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  PyTorch compile got faster? on dual 3090
Posted by: phaseport36 - 10-18-2026, 06:14 PM - Forum: PyTorch / JAX / Other Frameworks - Replies (6)

subscribed, curious where this lands.

I'm happy to test one more variant if you want a second data point.

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  routing between local and hosted: what are you seeing?
Posted by: plainworks - 10-18-2026, 06:13 PM - Forum: Recipes & Configurations - Replies (1)

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

This isn't revolutionary, but the combination of LM Studio and 5090 felt surprisingly usable once I tuned around MoE serving.

Maybe useful as a starting point for newer folks.

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