Anthropic is not a serious company lmao
@theahmadosman
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Model Inference: Kernels Execute The Actual AI Workload
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You don’t “run a model”
You run Kernels The model is just a graph The Inference Engine is scheduler / optimizer / executor But the actual work? That happens in the Kernels – MatMul Kernels
– Attention Kernels
– RMSNorm Kernels
– KV cache Kernels
– Quantized linear Kernels
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Skills: Elegant Automation for Large Language Models
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Skills are elegant automation for LLMs More people should use Skills to automate stuff
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7 Common Mistakes in Local Inference & Hardware
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7 Common Mistakes in Local Inference & Hardware
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Running Qwen 3.5 27B Locally on RTX 3090 GPU
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It’s called local inference, T. You just quantize Qwen 3.5 27B,
toss it on your RTX 3090,
and let that thing cook Context windows are for people who rent compute -
DeepSeek V4 Flash vs Qwen 3.6: Size vs Efficiency Showdown
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MADNESS DeepSeek V4 Flash 284B
(MoE, 13B Active Params/Tok) Is only 1 point higher on the Artificial Analysis Intelligence Index than Qwen 3.6 27B (Dense, 27B Active Param/Tok) Qwen 3.6 size is double that of the active parameters and 1/10 of the full size of DeepSeek V4 Flash -
Qwen 3.6 27B remains the top 2026 AI release with RTX 3090s
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Qwen 3.6 27B is still the release of 2026 for me despite everything else that has come out Pair it with a couple of RTX 3090s and you’re set even if they banned AI everywhere
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DeepSeek V4 Pro: Undertrained with less intelligence density than V3.2
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DeepSeek V4 Pro, for how massive it is (1.6T Parameters), is quite undertrained (32T Tokens) Yes, undertrained It has less intelligence density than that of V3.2 which is like 1/3rd of its size
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GPT-5.5 XHIGH optimizes DeepSeek 4 Flash on 4x DGX Sparks
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GPT-5.5 XHIGH is working hard right now to make vLLM runs DeepSeek 4 Flash on 4x DGX Sparks It got it to load, then had it answer cohesively on the 4x Sparks (though a tad too slow) Now, it optimizes it Letting this run overnight (in an engineered-harness specifically for it)
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Local RAG AI Stack Overview on RTX 3070 8GB
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Here is a high-level overview of my Local RAG / AI Knowledge Stack All hosted locally on a single RTX 3070 8GB btw Who is interested in a more in-depth breakdown? What would you like for it to cover?