14:50Stealth Ox Alpha: a new GLM model! Full test (coding & writing) against Grok, Gemini, GPT & others
Aug 21, 2026 · YouTube
30:13DeepSeek V4 Flash Vision: Low Price, but Does It Hallucinate?
Aug 21, 2026 · YouTube
51:00AI Coding Showdown: Grok 4.6, Gemini 3.7, Terra-Pro, Qwen3.8 2.4TB, Muse Glimmer & more
Aug 15, 2026 · YouTube
27:51Testing Gemini 3.7 Flash: Translation, Vision, and Coding Challenges
Aug 14, 2026 · YouTube
Inputs and files attached to the run itself. Model output is shown with its turn.
You are an expert automotive appraiser. Identify as many cars as possible in this image. Number each car and, for each, give: make, model, approximate year (a range is fine), and approximate average used price for that type of vehicle. Give a confidence level (high / medium / low) per car and say clearly when you are guessing. Work from the most clearly visible vehicles to the least.
As an automotive appraiser, I've surveyed the image from the foreground backward. I've numbered the vehicles below based on visual clarity, starting with the most recognizable and moving to the least. Please note that all used prices are approximate national averages for typical mileage and condition, and may vary significantly by region.
Car #1 (Foreground right, red pickup truck)
Car #2 (Silver compact SUV/crossover)
Car #3 (Dark gray sedan behind the RAV4)
Car #4 (Silver sedan behind the dark gray Camry)
Car #5 (Dark sedan further back, partially obscured)
Car #6 (Black SUV behind the dark sedan)
Car #7 (Red vehicle on the far left edge)