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Google DeepMind
Gemma 4 31B
gemma4-31b
Parameters: 31BQuantization: None (served in BF16)Context: 256K tokensStrengths: Image understanding, object detection, document parsing, OCR, chart comprehension, and pointingBest for: Image analysis, document understanding, OCR tasks, and visual reasoning with built-in thinking modeModel weights: google/gemma-4-31B-itConfiguration repo: tinfoilsh/confidential-gemma4-31b
Multimodal: Supports variable aspect ratios and configurable image token budgets for balancing speed and detail. See Image Processing Guide for usage examples.
Qwen
Qwen3-VL 30B
qwen3-vl-30b
Parameters: 30B (3B active)Quantization: None (served in BF16)Context: 256K tokensStrengths: Vision-language understanding, GUI interaction, screenshot-to-code generation, spatial understanding, multilingual OCROCR Languages: Supports 32 languagesBest for: Image analysis, screenshot-to-code generation, OCR tasks, GUI automation, and vision-text understandingModel weights: Qwen/Qwen3-VL-30B-A3B-InstructConfiguration repo: tinfoilsh/confidential-qwen3-vl-30b
Multimodal: Processes images with up to 256K context for long documents. See Image Processing Guide for usage examples.