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.
Here's my appraisal, working from most to least visible:
1. Ford Ranger (red, foreground right)
2. Nissan Murano (silver, center)
3. Hyundai Sonata (dark gray)
4. Toyota Camry (silver)
5. Gray sedan (behind the Camry)
6. Dark SUV (far left, background)
7. Red sedan (far left edge)
Note: Prices are rough US-market retail averages for vehicles in average condition and vary significantly by mileage, trim, and region.