> ## Documentation Index > Fetch the complete documentation index at: https://docs.getjumper.io/llms.txt > Use this file to discover all available pages before exploring further. # List of Machine Learning Models > Jumper uses powerful AI models to help you search through your videos visually. These models understand what's in your footage and let you find moments using natural language. ## Visual models This is a more comprehensive list of the models and their properties. | **Model Name (Display)** | **Resolution** | **Size on Disk** | **Information** | | :----------------------------- | :------------- | :---------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Ultra Accurate** | — | Download required | **Highest-accuracy visual model.** A different architecture from the V1/V2 models below. State-of-the-art search quality on Apple silicon Macs and Windows. Requires more compute and produces larger analysis files than the Accurate presets. Not available on Intel Macs. | | **V2 Medium (Default)** | 256×256 | \~1.5GB | **Default, bundled in app installer**
Balanced accuracy vs. performance, improved semantic understanding from V2 model improvements. Works well on most modern computers. | | **V2 Multilingual x-high-res** | 512x512 | \~2GB | Excellent search result quality in both non-English **and** English languages. Benefits from more detailed and "verbose" searches - e.g. "a metal sign saying XYZ" instead of just "XYZ" | | **V1 Multilingual high-res** | 384x384 | \~4GB | Very accurate search result quality in both non-English **and** English languages. Benefits from more detailed and "verbose" searches - e.g. "a metal sign saying XYZ" instead of just "XYZ" | | **V2 Medium high-res** | 384×384 | \~1.5GB | Identical parameter count as V2 Medium but will analyze frames at 384×384 for more image detail. Good if you need slightly finer detail than 256×256, but be aware it requires more RAM/VRAM. | | **V2 Medium x-high-res** | 512×512 | \~1.5GB | Same parameter count as V2 Medium, but even higher resolution (512×512). Ideal for text detection/OCR or detailed reverse image searches. Uses significantly more memory and produces larger analysis files. | | **V2 Large** | 256×256 | \~3.3GB | Larger model with higher accuracy in challenging scenarios. | | **V2 Large high-res** | 384×384 | \~3.3GB | Same as V2 Large but with higher resolution (384×384). Ideal for text detection/OCR or detailed reverse image searches. | | **V2 Large x-high-res** | 512×512 | \~3.3GB | Same parameters as V2 Large, but at 512×512 input resolution. Ideal for text detection/OCR or detailed reverse image searches. | | **V2 XLarge** | 256×256 | \~4.5GB | Even larger V2 model. Offers improved recognition of subtle elements. Ideal if you want top-tier accuracy and have the computer to run it. | | **V2 XLarge high-res** | 384×384 | \~4.5GB | A higher-resolution variant of V2 XLarge. | | **V2 XLarge x-high-res** | 512×512 | \~4.5GB | The heaviest V2 model in terms of resolution and parameter requirements. Even more accurate, even more resource demanding. | | **Medium** | 256×256 | \~812MB | Legacy previous default model (V1), previously bundled with the application. Reasonably accurate but outperformed by V2 Medium in most scenarios. If your hardware can handle V2 Medium, prefer that instead. | | **Medium x-high-res** | 512×512 | \~812MB | Same as V1 Medium but at 512×512. Useful for text detection, reverse image searches, etc. Produces larger analysis files than some bigger V1 models, purely due to the higher frame resolution. | | **Large multilingual** | 256×256 | \~1.48GB | V1 Multilingual version that improves accuracy for non-English text. V2 equivalents are multilingual by default. | | **Large** | 256×256 | \~2.61GB | Larger V1 model. Prefer V2 alternatives. | | **Large high-res** | 384×384 | \~2.61GB | Same as V1 Large but higher resolution. Demands more resources. | | **XLarge high-res** | 384×384 | \~3.51GB | Largest V1 model. High accuracy, but overshadowed by the new V2 XLarge. Recommended only for legacy compatibility if you can't run V2. | | **XLarge multilingual** | 256×256 | \~4.51GB | Largest V1 multilingual model. Very high accuracy for non-English searches - V2 models are multilingual by default, but V1 multilingual models can be slightly better than V2 models on certain languages. | ## Speech models For transcriptions, Jumper uses **Whisper** models developed by OpenAI. The exact model depends on your platform. | **Platform** | **Model Variant** | **Size on Disk** | **Notes** | | :---------------------- | :--------------------- | :--------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **Windows / Intel Mac** | whisper-large-v3-turbo | \~1.62GB | Bundled with Windows and Intel Mac installers. | | **Apple M-series Macs** | whisper-large-v3-turbo | \~467MB | Uses a quantized version converted to Apple's MLX framework for hardware acceleration (faster analysis, smaller model size). Bundled with Apple M-series installer. | ### Language-specific models Beyond the default Whisper model, Jumper offers more accurate speech-to-text models for specific languages, including Chinese (20+ dialects), Arabic, Hindi, Cantonese, Korean, Thai, Vietnamese, Filipino, and Russian. Some languages also have state-of-the-art fine-tuned models, including Japanese, Swedish, and Moroccan Arabic (Darija). When a dedicated model is available for the language you're transcribing, selecting that language during analysis gives more accurate results than auto-detection. For the full language list, see [Supported Languages](/reference/supported-languages).