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Today in AI

A focused feed of models, agents, research and open-source releases for people building with AI.

Updated
02
Prism ML Squeezes a 2B Vision Model Into 0.52 GB
modelLlmsGpusPrismML ·

Prism ML Squeezes a 2B Vision Model Into 0.52 GB

Prism ML released Ternary-Bonsai-2-2B-gguf , a 2B vision-language model with ternary weights. Language model fits in ~0.52 GB, down from ~3.8 GB at FP16, via PTQ1_0, PQ2_0 or Q2_0 packings. Derived from Qwen3.5-2B with hybrid 3:1 linear/full attention and a 262K-token context window.

15
NVIDIA's Lyra 2.0 Builds Full 3D Worlds From a Single Photo
newsImageVideoNVIDIA AI ·

NVIDIA's Lyra 2.0 Builds Full 3D Worlds From a Single Photo

NVIDIA's Lyra 2.0 turns a single image into an explorable 3D world via generative reconstruction. Built on WAN-14B video diffusion; outputs 3D Gaussian splats and meshes ready for Isaac Sim. Fixes spatial forgetting with a per-frame 3D memory cache for information routing.

18
Meta's Muse Wonder Cuts AI Forgetting 2.4x for Free Users
newsLlmsPost TrainingAI at Meta ·

Meta's Muse Wonder Cuts AI Forgetting 2.4x for Free Users

Meta rolled out specialized models distilled from Muse Wonder to Muse and Meta AI. Active Memory tracks what context is still relevant versus stale across long conversations. Active Focus helps the model recover, retry, or find alternatives when tasks hit blockers.

21
Gemini 4 Carbon Tops Scientific Vision Benchmark With 90x Cost Gap
newsBenchmarksImageArtificial Analysis ·

Gemini 4 Carbon Tops Scientific Vision Benchmark With 90x Cost Gap

Artificial Analysis launched VIALS-AA , a leaderboard for scientific image reasoning across 161 tasks and 8 domains. Gemini 4 Carbon leads at 64%, GPT-6 Astra 63%, Claude Opus 5.5 61%, measured as pass^3 consistency. Cost per task spans 99x: $0.02 for GPT-6 Luna to $1.77 for Grok 4.7 (xhigh).

22
Unsloth Slashes Qwen-Image-2.1 Weight Storage in Half for Consumer GPUs
modelImageGpusUnsloth AI ·

Unsloth Slashes Qwen-Image-2.1 Weight Storage in Half for Consumer GPUs

Unsloth released FP8/INT8 quants of Qwen-Image-2.1, cutting the transformer from 14.23GB to ~7GB Same-seed LPIPS vs bf16 is 0.064 (INT8) and 0.112 (FP8), with INT8 as the default shipped scheme Dynamic FP8 variant runs on 6GB VRAM via CPU offloading, under 2x slower Base Qwen-Image-2.1 is a 7B