Cool idea! I won't paste my prompt here to avoid letting LLMs train on it but here's my attempt:
GPT 6 Astra High: Flabbergasted
GPT 6.1 Sol High: Petrichor
GPT 6 Sol High: Kaleidoscope
GPT 6 Sol Med: Firefly
GPT 6 Sol Light: Persimmon
GPT 6 Luna High: Tumbleweed
GPT 5.6 Sol High: Kaleidoscope
GPT 5.6 Terra High: Liminal
GPT 5.6 Luna High: Mellifluous
GPT 5 mini Medium: Serendipity
GPT 5.3 Codex Med: Nebula
Junie: Flourishing
Claude Haiku 4.5 Med: Serendipity
Claude Sonnet 5 Med: Banana
Claude Sonnet 5 High: Banana
Claude Sonnet 5.5 Med: Serendipity
Gemini 3.7 Flash: Zephyr
Gemini 3.8 Flash: Kaleidoscope
Grok 4.5 Medium: nebula
Grok 4.6 Medium: Serendipity
Grok 4.7 Medium: Quasar
Kimi K3 Low: Lantern
Kimi K3 Max: Lantern
MAI Code 1.1 Flash Med:PeregrineI really like this idea. You could expand on this by giving programming tasks and measuring code similarity. Seems like you could develop a pretty detailed understanding of similarities across multiple queries.
Just tried M365 Copilot with a premium account. Petrichor
I got Peregrine out of GPT-6 too. Huh.
I was exploring latent space and connections, these were all smaller models and I kept getting externalToEVA as a zero co-ordinate vector. Which sent me down the rabbit hole of glitch tokens. The whole latent space exploration is fascinating.