Topic
Local LLM
84 posts on local llm — guides and lab notes from real runs on hardware we own. New posts land here automatically. Start anywhere, or grab the copy-paste prompts that ship with them.
- 5 min read
A 27B Model Fit on an 8 GB GPU. It Was Slow.
Qwen3.8-27B Q3_K_S loaded on an RTX 3070. VRAM used 7,435 of 8,192 MiB. Decode ran 2.07 tok/s. Fit on 8 GB is not a usable rate.
- 4 min read
My Local LLM Writer Failed Its Own Word-Count Gate
Gemma 4 26B wrote a 535-word draft against a 550-word floor. The gate blocked it, both rescue engines were down, and no bad post shipped.
- 5 min read
Unload Local LLMs After Every Test
A local model test is not over when text appears. I unload the model, read idle VRAM, and record the result before I start another run.
- 5 min read
How I Benchmark Local LLMs Before I Trust Them
A local LLM benchmark should end with a decision. I record task quality, tokens per second, VRAM, power, and failure state before I add a model.
- 5 min read
How I Test a 30B Local Model Before I Load It
A 30B local model can fit on paper and still fail the job. This test plan checks memory, tool use, speed, and repeatability first.
- 5 min read
When a 4B Local LLM Beats 26B on One Task
On one RTX 5090 workshop, a 4B model beat a 26B model on speed while both passed four code checks. Here is the model-selection rule I kept.
- 5 min read
Does Ollama Include That New llama.cpp Feature?
A llama.cpp release note does not prove that Ollama can use the feature. I trace the active runtime path, pin versions, and test the same workload.
- 5 min read
My Local LLM Got Faster After It Passed the Tests
A three-run RTX 5090 test showed why local LLM tuning must pair speed with fixed-task checks. One faster setting also repaired every test.
- 6 min read
My local models refused zero of 50 security tasks
Hosted coding assistants have declined defensive security work. I ran 50 such tasks across five local models on my own hardware and counted zero refusals.
- 5 min read
The faster local model run took 83x longer
One llama3.1:8b run posted 188.16 tok/s and finished in 43.9 seconds. The next posted 153.12 and finished in 0.53. Tokens per second ranked them backwards.
- 6 min read
Chunk Size Is a Reliability Setting
Three native crashes destroyed seven hours of compute on a fully offline OCR run. The fix was not more parallelism. It was a smaller unit of work.
- 5 min read
Why Local LLM Benchmarks Need Power Data
A local LLM benchmark that reports only tokens per second hides the operating cost. My RTX 5090 run shows what power data adds.
The AI agent build notes
Real costs, real tools, no fluff. One evidence-backed note on Friday when there is something worth sharing.
Get the requested artifact now, then at most one evidence-backed Local AI Lab Note on Friday when there is something worth sharing. One-click unsubscribe. No sponsored placements. Privacy.