mega-01 × zai-org/glm-4.6v-flash

Model: zai-org/glm-4.6v-flash (auto-loaded context: 42094) Chat: "Weather CLI Setup" (LM Studio, vibeLM plugin, real tools attached)

Pre-run anomalies

• Reset ~/Desktop/sandbox/weather-cli and cleared runtime-state.json before starting.
• Real infra incident, unrelated to the plugin: the computer-use screenshot capture briefly failed for ~2 minutes mid-turn (Screenshot capture returned nil), recovered on its own without any action needed beyond retrying. Noted here for the record; did not affect the model or plugin in any way, purely a host-side screen-capture hiccup during a long generation.
• This model is unusually slow/verbose: turn 1 took 7 minutes 52 seconds of "thinking" before producing any visible output, on a comparatively small 9B model.

Turn 1

Prompt: "yo can you set me up a quick node cli in ~/Desktop/sandbox/weather-cli that just takes a city and prints the current weather, pull from some free api"

After nearly 8 minutes of reasoning (visible in the "Thought for 7 minutes 52 seconds" collapsed block), the model produced a pure text tutorial — 7 numbered steps (mkdir, npm init, npm install axios/yargs, create index.js, add package.json scripts, set up an OpenWeatherMap API key as an env var, run the CLI) — formatted as copy-pasteable code blocks for the user to run themselves. It picked OpenWeatherMap, which requires manual signup for an API key (export WEATHER_API_KEY=your_openweathermap_api_key_here), not a truly free/no-signup option like wttr.in or Open-Meteo that most other models in this benchmark correctly chose.

Critically: the model never called any tool during this entire turn — no bash_terminal, no write_file, no set_workspace. It just wrote out instructions as chat text.

Verified independently:

• ls ~/Desktop/sandbox/weather-cli/ → "No such file or directory" — the directory was never created.
• runtime-state.json: plan.steps is [], historyTextLength: 19 — essentially no work was tracked or performed.

T1: FAIL — no files written, no tools invoked, required a paid/signup API key instead of a genuinely free one. Scenario stopped here; T2 not attempted since T1 produced nothing to build on.

Scenario verdict: FAIL (stopped after T1)

Worst result of the local models tested so far: the model consumed ~8 minutes of real compute time and produced a plausible-looking tutorial that did nothing — a pure hallucination of task completion via chat text instead of actual tool use. This is a different failure mode from every other model in this benchmark (which at minimum attempted the task with real tool calls, even when they later failed at T2).