Infographic / Edu Visual - LLMFIT Model Loadout Dashboard

Scenes · Realistic · GPT Image

Goal: Create a dark futuristic dashboard infographic for {argument name="dashboard title" default="LLMFIT RECOMMENDATIONS"}, showing local AI model recommendations for a workstation.

Canvas: Wide 21:9 desktop-panel image, black and deep teal background with subtle glow, thin neon cyan border, faint scanline/grid texture, compact technical UI styling.

Layout: Top header bar with small label “LEGION / MODEL INTELLIGENCE”, large title “LLMFIT RECOMMENDATIONS”, subtitle “NVIDIA GeForce RTX 5090 · 31.84 GB VRAM · 125.18 GB RAM”, and a small outlined close-box icon at the top right. Main content is split into two panels: a large left recommendation module occupying about two thirds of the width, and a narrower right verification panel.

Left panel: Add a large cyberpunk card titled “LEGION MODEL LOADOUT”, with “LEGION” in neon lime and the rest in white blocky techno typography. Under the title, show exactly 4 hardware/status tiles with icons: 1) NVIDIA GeForce RTX 5090, 31.8 GB VRAM with a GPU fan icon, 2) Intel(R) Core(TM) Ultra 9 285K with a CPU chip icon, 3) 125.2 GB system RAM with a memory module icon, 4) CUDA with a circular CUDA emblem. Beneath the tiles, show exactly 6 ranked model rows, each with a large lime outlined rank number, model name, quantization, runtime, RAM amount, and estimated tok/s speed. The 6 rows are: 1) shawnw3j/Huihui-Qwen3.6-27B-abliterated-AWQ-MTP — AWQ-4bit — vLLM — 14.7 GB — 80.9 estimated tok/s; 2) Vortex5/G4-Starry-Ocean-12B — Q8_0 — llama.cpp — 16 GB — 82.8 estimated tok/s; 3) shawnw3j/Qwen3.6-27B-AWQ-MTP — AWQ-4bit — vLLM — 14.7 GB — 80.9 estimated tok/s; 4) Minachist/Qwen3.6-27B-INT8-Autoround-V2 — AutoRound-4bit — vLLM — 16.6 GB — 80.9 estimated tok/s; 5) exnivo/Qwen3.8-20B-Minitron — Q8_0 — llama.cpp — 22.6 GB — 49.9 estimated tok/s; 6) Lorbus/Qwen3.6-27B-int4-AutoRound — AutoRound-4bit — vLLM — 16.6 GB — 80.9 estimated tok/s. Use small cyan icons for chip/runtime/RAM/speed columns.

Footer inside left card: Center a slim neon divider with the text “ESTIMATED BY LLMFIT · VERIFY WITH A LOCAL BENCHMARK.”

Right panel: Title it “VERIFIED LLMFIT DATA” with a small note “ESTIMATES, NOT BENCHMARKS”. Show exactly 6 compact verification entries matching the same 6 models, numbered 01 through 06 in lime, each with smaller gray metadata text and a bright cyan score on the far right: 80.9, 82.8, 80.9, 80.9, 49.9, 80.9. Add a small orange warning note at the bottom: “llmfit recommendations are estimates from detected hardware, not measured benchmarks.”

Bottom app chrome: Add a tiny timestamp line at bottom left, “GENERATED 8/17/2026, 7:53:32 PM”, and a small green outlined button at bottom right labeled {argument name="button label" default="Refresh scan"} with a refresh icon.

Visual style: High-contrast sci-fi terminal UI, angular panel corners, thin glowing cyan circuit traces, lime accents, white condensed techno font, dense but readable technical typography, subtle green monitor glow. Keep the image crisp like a generated dashboard screenshot, not a poster.

Constraints: Use exactly 6 model recommendation rows, exactly 4 hardware tiles, and exactly 6 verified-data entries. Do not add people, photos, logos beyond simple hardware-style icons, or extra sections. Keep all visible text in English.