Image generators remember more than the output.
A generation request reads as a transaction — input in, image out, nothing left behind.
The prompt is the part that doesn't leave.
It stays attached to an account, accumulates across sessions, builds a record the user never explicitly authored.
The model learns the aesthetic before the user names it.
I hadn't thought about what that implied until a platform surfaced my style preferences back to me.
Prompts from three weeks earlier, repackaged as a profile. The granularity was specific enough that I recognized the pattern — but I hadn't constructed it consciously.
It assembled from requests I treated as separate, unrelated, temporary.
A behavioral signature — not an image.
OpenGradient Chat kept surfacing around exactly this question — how the infrastructure handles the prompt before the model sees it.
Image Studio in OpenGradient Chat sits behind TEE infrastructure — the operator cannot read the prompts.
Not something the operator chose. The architecture doesn't give them access to choose. Gemini, ByteDance, xAI — three different model integrations, same condition underneath.
The session ends. Nothing that connected the prompt to an account stays behind.
Whether that holds under real load across all three, I haven't verified independently.
The attestation covers the gateway.
What happens before the prompt arrives — whether the enclave assumption stays intact across updates.
Nobody has published a test for that condition yet.
$OPG #OPG @OpenGradient
A generation request reads as a transaction — input in, image out, nothing left behind.
The prompt is the part that doesn't leave.
It stays attached to an account, accumulates across sessions, builds a record the user never explicitly authored.
The model learns the aesthetic before the user names it.
I hadn't thought about what that implied until a platform surfaced my style preferences back to me.
Prompts from three weeks earlier, repackaged as a profile. The granularity was specific enough that I recognized the pattern — but I hadn't constructed it consciously.
It assembled from requests I treated as separate, unrelated, temporary.
A behavioral signature — not an image.
OpenGradient Chat kept surfacing around exactly this question — how the infrastructure handles the prompt before the model sees it.
Image Studio in OpenGradient Chat sits behind TEE infrastructure — the operator cannot read the prompts.
Not something the operator chose. The architecture doesn't give them access to choose. Gemini, ByteDance, xAI — three different model integrations, same condition underneath.
The session ends. Nothing that connected the prompt to an account stays behind.
Whether that holds under real load across all three, I haven't verified independently.
The attestation covers the gateway.
What happens before the prompt arrives — whether the enclave assumption stays intact across updates.
Nobody has published a test for that condition yet.
$OPG #OPG @OpenGradient