Jev versus text-generating models
Jev does not generate free-form text. A side-by-side video compares parallel decision-making with token-by-token text generation.
Using Braille Characters to Let Text-Only Jev Understand Shapes
The author tries to get Jev, which is text-only with no image input, to understand basic shapes: render a shape to a 64×64 canvas, threshold it, and pack each 2×4 pixel block into a Unicode braille glyph, turning the image into 512 plain-text characters fed to Jev.
Can Jev understand basic shapes? Kind of. Jev is text-only. No image input at all. So I cheated. Render a shape to a 64×64 canvas, threshold it, and pack every 2×4 block of pixels into a Unicode braille glyph. The picture becomes 512 characters of plain text, which Jev can
· 0 likesOpen on X
More like this
Pricing, evaluations, and the name Jev
The launch thread explains code-and-AI workflow evaluations, the input price announced at launch, and free output tokens.
Jev Model: Decision-Making Probability Generation, 200× Faster and 400× Cheaper Than LLMs
This model is built for decision-making rather than text generation, outputting probabilities for each option in parallel instead of token-by-token responses. The author shares a simplified comparison of normal LLMs versus this Jev model.
