Topic
5090 Reports
23 posts on 5090 reports — 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
Why production AI is moving to open weights
I tested a local-first writing pipeline on an RTX 5090. Gemma 4 writes the draft, deterministic checks catch errors, and frontier QA decides what ships.
- 5 min read
Q4km vs Q5km: Q4_K_M vs Q5_K_M
q4km vs q5km is Q4_K_M vs Q5_K_M in GGUF. Pick by VRAM headroom, quality risk, and CPU fallback. Use the free quant tool before download.
- 6 min read
My 8B Model Failed a 400-Word Task
Three Llama 3.1 8B runs missed a 400-word floor. Here is the verifier-driven route that moved long-form synthesis to Gemma 4 26B.
- 5 min read
I Raised the QA Bar on Blog Infographics
Blog charts need correct labels. I tightened layout geometry, char budgets, claims checks, and vision logs so a bad PNG cannot ship quietly.
- 6 min read
Pin Your Local LLM Context Size Before You Build a Router
Changing context size can reload a local model before every request. A measured RTX 5090 sweep shows why context belongs in the routing key.
- 5 min read
Local LLMs Need a Timeout Before They Need a Bigger Model
A bigger local model will not fix a stuck runtime. Add a bounded inference doctor first, then trust the benchmark.
- 5 min read
A verifier loop beats a faster local model
Local LLMs are useful when the loop proves the output, not when the benchmark looks good. This is the small gate I use before a local coding agent gets more rope.
- 4 min read
How I Gate a Local Coding Model Before I Trust It
A local model is not ready because it runs fast. It is ready when one verifier loop can prove the output before an agent writes files.
- 5 min read
How to Make a Local QLoRA Starter Fail Safely
A local QLoRA starter should prove data, GPU safety, metrics, tests, and blockers before it claims progress. Here is the small loop I use on owned hardware.
- 5 min read
How to Run Local LLM Verifier Loops on Owned Hardware
A local LLM workflow needs more than a model prompt. It needs a verifier loop that proves the file, command, URL, or report changed before the agent claims done.
- 7 min read
llama.cpp --n-gpu-layers: -1, 0, Partial
Set --n-gpu-layers in llama.cpp with clear -1, 0, and partial offload rules, VRAM headroom checks, examples, and CPU fallback fixes.
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