[bmdpat]

/* ------------------------------------------------ */

BMD

// build. measure. deploy.

*/

A real shell running in your browser. Type desk to size your GPU, or tap a command. The bench replay streams at the measured rate. It is a replay, not a live model.

pat@5090:~$ cat latest_sweep.md

THE 5090 REPORTS // the lab notes behind the desk

I run open models on my own GPUs and publish the results.

Each report shows the model, quant, prompt, hardware, speed, VRAM use, and what broke. AgentGuard handles spend limits, loops, timeouts, and rate limits.

Read the 5090 Reports

pat@5090:~$ column -t fig1_sweep.tsv

Headline run01 / 06
Model
llama3.1:8b
Quant
Q4_K_M
Generation
228.9 TOK/S
Peak VRAM
7.2 GB
Open all six measured rows
Fig. 1 Six runs on the RTX 5090, Ollama 0.31.1, temperature 0. llama3.1:8b Q4_K_M reached 228.9 tok/s generation, measured 2026-07-09.Raw artifact

pat@5090:~$ tail -n 1 stderr.log

[WARN] stderr

Changing num_ctx between requests forces a full model reload. On a 26B that is 140 seconds per swap. Pin your context size.

Field note, 2026-07-09

pat@5090:~$ agentguard --status

I use AgentGuard to stop spend, loops, timeouts, and rate-limit failures before a test touches real work.

$ pip install agentguard47

pat@5090:~$ ls tools/

pat@5090:~$ ps aux | grep agents

§ 004 / OPERATING LOOP

One person. Small tools. Agent-assisted ops.

01

Run

Run the model on the target GPU.

02

Measure

Record tokens, latency, VRAM, cost, and failure mode.

03

Publish

Write up the result or ship the tool it required.

pat@5090:~$ tail blog.log

§ 005 / BUILD NOTESloading

Build notes.

Loading the latest notes…

pat@5090:~$ mail -s "subscribe" pat@5090

To: the journal // Subj: subscribe

Get the journal by email.

New benchmark results, failed runs, VRAM checks, and tools. I send an email only when there is a real result.

Get the Local AI Field Kit

Four copy-ready tools now, then one evidence-backed Local AI Lab Note on Friday when there is something worth sharing.

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[bmdpat] 0:desk*VRAM 7.8/32.0 GB