Supported Models
Every model below ships pre-exported in the models registry and downloads on first use. Backends: XNNPACK (CPU, iOS and Android), Core ML and MLX (iOS), Vulkan (Android GPU); DEFAULT picks the fastest one the device can run. Any other ExecuTorch .pte can be loaded too, see Exporting Custom Models.
LLMs & VLMs
Chat sessions stream tokens and support tool calling, a thinking-mode switch, Jinja chat templates, constrained sampling and image/audio inputs on multimodal models.
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.llm.MINICPM5_2B | OpenBMB MiniCPM5 2B chat model with an 8K context window. | XNNPACK, MLX | 8da4w, int4 | v0.11.0 |
models.llm.LFM2_5_1_2B | Liquid AI LFM 2.5 1.2B general-purpose hybrid language model. | XNNPACK, MLX | 8da4w, int4 | v0.8.0 |
models.llm.LFM2_5_2_6B | Liquid AI LFM 2.5 2.6B hybrid language model post-trained for instruction following and agentic workloads. | XNNPACK, MLX | 8da4w, int4 | v0.11.0 |
models.llm.LFM2_5_350M | Liquid AI LFM 2.5 350M ultra-compact hybrid language model. | XNNPACK, MLX | 8da4w, int4 | v0.8.1 |
models.llm.LFM2_5_VL_450M | Liquid AI LFM 2.5 VL 450M lightweight multimodal vision-language model. Inputs: text, image. | XNNPACK, MLX, Vulkan | 8da4w, int4 | v0.8.4 |
models.llm.LFM2_5_VL_1_6B | Liquid AI LFM 2.5 VL 1.6B high-capacity vision-language model. Inputs: text, image. | XNNPACK, MLX, Vulkan | int8, 8da4w, int4 | v0.8.4 |
models.llm.BIELIK_V3_1_5B | Bielik v3 1.5B bilingual Polish & English language model, developed by SpeakLeash. | XNNPACK | 8da4w | v0.9.0 |
models.llm.LLAMA3_2_1B | Meta Llama 3.2 1B lightweight instruction-tuned multilingual model. | XNNPACK, MLX | int4, spinquant | v0.1.0 |
models.llm.LLAMA3_2_3B | Meta Llama 3.2 3B instruction-tuned multilingual language model. | XNNPACK, MLX | int4, spinquant | v0.1.0 |
models.llm.SMOLLM2_135M | Hugging Face SmolLM2 135M ultra-compact language model. | XNNPACK, MLX | int8, 8da8w | v0.4.1 |
models.llm.SMOLLM2_360M | Hugging Face SmolLM2 360M compact instruction-tuned model. | XNNPACK, MLX | int8, 8da8w | v0.4.1 |
models.llm.SMOLLM2_1_7B | Hugging Face SmolLM2 1.7B language model trained on curated educational, synthetic, and web data. | XNNPACK, MLX | int8, 8da8w | v0.4.1 |
models.llm.HAMMER2_1_0_5B | Hammer 2.1 0.5B specialized function-calling model. | XNNPACK, MLX | 8da4w, int4 | v0.4.1 |
models.llm.HAMMER2_1_1_5B | Hammer 2.1 1.5B function-calling language model. | XNNPACK, MLX | 8da4w, int4 | v0.4.1 |
models.llm.HAMMER2_1_3B | Hammer 2.1 3B high-capacity function-calling model. | XNNPACK, MLX | 8da4w, int4 | v0.4.1 |
models.llm.PHI4_MINI | Microsoft Phi-4 Mini 3.8B high-density reasoning model. | XNNPACK, MLX | 8da4w, int4 | v0.4.1 |
models.llm.QWEN2_5_0_5B | Alibaba Qwen 2.5 0.5B ultra-lightweight multilingual model. | XNNPACK, MLX | 8da4w, int4 | v0.4.1 |
models.llm.QWEN2_5_1_5B | Alibaba Qwen 2.5 1.5B multilingual instruction model. | XNNPACK, MLX | 8da4w, int4 | v0.4.1 |
models.llm.QWEN2_5_3B | Alibaba Qwen 2.5 3B high-capability multilingual model. | XNNPACK, MLX | 8da4w, int4 | v0.4.1 |
models.llm.QWEN3_0_6B | Alibaba Qwen 3 0.6B next-generation compact language model. | XNNPACK, MLX | int8, 8da4w | v0.4.1 |
models.llm.QWEN3_1_7B | Alibaba Qwen 3 1.7B next-generation multilingual language model. | XNNPACK, MLX | 8da4w, int4 | v0.4.1 |
models.llm.QWEN3_4B | Alibaba Qwen 3 4B high-capacity generative model. | XNNPACK, MLX | 8da4w, int4 | v0.4.1 |
models.llm.GEMMA4_E2B | Google Gemma 4 E2B generative language model. | XNNPACK, MLX, Vulkan | 8da4w, int4 | v0.9.1 |
models.llm.GEMMA4_OMNI_E2B | Google Gemma 4 E2B multimodal (omni) language model supporting text, image, and audio inputs. Inputs: text, image, audio. | XNNPACK, MLX, Vulkan | 8da4w, int4 | v0.9.1 |
Text Embeddings
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.textEmbeddings.ALL_MINILM_L6_V2 | Compact 384-dimensional sentence transformer mapping text to a dense vector space. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.4.1 |
models.textEmbeddings.ALL_MPNET_BASE_V2 | High-quality 768-dimensional sentence transformer model based on MPNet. | XNNPACK, Vulkan | fp16, int8, 8da4w | v0.4.1 |
models.textEmbeddings.MULTI_QA_MINILM_L6_COS_V1 | 384-dimensional sentence transformer fine-tuned specifically for semantic QA matching using cosine similarity. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.4.1 |
models.textEmbeddings.MULTI_QA_MPNET_BASE_DOT_V1 | 768-dimensional sentence transformer fine-tuned specifically for question-answering matching using dot product distance. | XNNPACK, Vulkan | fp16, int8, 8da4w | v0.4.1 |
models.textEmbeddings.PARAPHRASE_MULTILINGUAL_MINILM_L12_V2 | 384-dimensional sentence transformer supporting 50+ languages for cross-lingual semantic similarity. | XNNPACK, Core ML, Vulkan | fp16, int8, 8da4w | v0.9.0 |
models.textEmbeddings.DISTILUSE_BASE_MULTILINGUAL_CASED_V2 | Multilingual sentence transformer supporting 50+ languages, based on distilled Universal Sentence Encoder (512-dim output). | XNNPACK, Core ML, MLX, Vulkan | fp16, int8, 8da4w | v0.9.0 |
models.textEmbeddings.CLIP_VIT_BASE_PATCH32_TEXT | CLIP text encoder (ViT-B/32) mapping text queries into a 512-dimensional joint text-image embedding space. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.3.4 |
models.textEmbeddings.LFM2_5_EMBEDDING_350M | Liquid AI LFM 2.5 350M parameter embedding model for asymmetric search and retrieval tasks. | XNNPACK, MLX | 8da4w, int4 | v0.10.0 |
ColBERT Retrieval
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.colbertEmbeddings.LFM2_5_COLBERT_350M | Liquid AI LFM 2.5 350M ColBERT model: 128-dimensional token vectors, multilingual (11 languages), 32-token queries and documents of up to 512 tokens. | XNNPACK, MLX | 8da4w, int4 | v0.11.0 |
Privacy Filter (PII detection)
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.privacyFilter.OPENAI | OpenAI-style detector covering 8 common PII types (name, email, phone, address, and similar). | XNNPACK, MLX | 8da4w, int4 | v0.9.0 |
models.privacyFilter.NEMOTRON | Nemotron-based detector covering 55 fine-grained PII types. | XNNPACK, MLX | int8, 8da4w | v0.9.0 |
Speech to Text
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.speechToText.WHISPER | OpenAI Whisper automatic speech recognition model family with integrated Voice Activity Detection. Variants: TINY, BASE, SMALL, EN.TINY, EN.BASE, EN.SMALL. | XNNPACK, Core ML, MLX, Vulkan | fp16, bf16, int8 | v0.3.0 |
Text to Speech
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.textToSpeech.SUPERTONIC | Supertonic 3 multilingual flow-matching Text-to-Speech model. | XNNPACK, MLX, Vulkan | fp32, fp16, int8 | v0.10.0 |
models.textToSpeech.KOKORO | Kokoro — a lightweight phoneme-driven Text-to-Speech model. Variants: EN_US, EN_GB, ES, FR, IT, PT, HI, PL, DE, ZH. | XNNPACK, Core ML | fp32 | v0.7.0 |
Voice Activity Detection
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.voiceActivityDetection.FSMN_VAD | Feedforward Sequential Memory Network (FSMN) Voice Activity Detection model. | XNNPACK | fp32 | v0.6.0 |
Image Classification
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.classification.EFFICIENTNET_V2_S | EfficientNetV2-S image classification model pre-trained on ImageNet-1k (1000 categories, see IMAGENET1K_LABELS). | XNNPACK, Core ML | fp16, int8 | v0.2.0 |
Object Detection
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.objectDetection.SSDLITE320_MOBILENET_V3_LARGE | SSDLite object detector with MobileNetV3-Large backbone trained on COCO (see COCO_CLASSES) at 320x320 resolution. | XNNPACK, Core ML | fp32, fp16 | v0.2.0 |
models.objectDetection.RFDETR_NANO | RF-DETR (Roboflow Detection Transformer) Nano variant trained on COCO (see COCO_CLASSES). | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.8.0 |
models.objectDetection.YOLO26 | Ultralytics YOLO26 real-time object detection models trained on COCO (80 classes, see COCO_CLASSES_YOLO). Variants: NANO, SMALL, MEDIUM, LARGE, XLARGE (each SIZE_384, SIZE_512, SIZE_640). | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.8.0 |
Instance Segmentation
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.instanceSegmentation.FASTSAM | Fast Segment Anything Model (FastSAM) for promptable or global object instance mask segmentation. Variants: S, X. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.9.0 |
models.instanceSegmentation.RFDETR_NANO | RF-DETR (Roboflow Detection Transformer) Nano instance segmentation model predicting COCO class masks and bounding boxes (see COCO_CLASSES). | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.8.0 |
models.instanceSegmentation.YOLO26 | YOLO26 instance segmentation models predicting COCO class instance masks and bounding boxes (see COCO_CLASSES_YOLO). Variants: NANO, SMALL, MEDIUM, LARGE, XLARGE (each SIZE_384, SIZE_512, SIZE_640). | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.8.0 |
Semantic Segmentation
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.semanticSegmentation.SELFIE_SEGMENTATION | Lightweight portrait selfie segmentation model for real-time person vs background separation. | XNNPACK, Core ML | fp32, fp16 | v0.8.0 |
models.semanticSegmentation.SELFIE_SEGMENTATION_LANDSCAPE | MediaPipe Selfie Segmentation, landscape orientation. | XNNPACK, Core ML | fp32, fp16 | v0.10.0 |
models.semanticSegmentation.LRASPP_MOBILENET_V3_LARGE | Lite R-ASPP semantic segmentation model with MobileNetV3-Large backbone (21 classes, see PASCAL_VOC_LABELS). | XNNPACK, Core ML | fp16, int8 | v0.8.0 |
models.semanticSegmentation.DEEPLAB_V3_RESNET50 | DeepLabV3 semantic segmentation model with ResNet-50 backbone (21 classes, see PASCAL_VOC_LABELS). | XNNPACK, Core ML | fp16, int8 | v0.4.1 |
models.semanticSegmentation.DEEPLAB_V3_RESNET101 | DeepLabV3 semantic segmentation model with ResNet-101 backbone (21 classes, see PASCAL_VOC_LABELS). | XNNPACK, Core ML | fp16, int8 | v0.8.0 |
models.semanticSegmentation.DEEPLAB_V3_MOBILENET_V3_LARGE | DeepLabV3 semantic segmentation model with MobileNetV3-Large backbone (21 classes, see PASCAL_VOC_LABELS). | XNNPACK, Core ML | fp16, int8 | v0.8.0 |
models.semanticSegmentation.FCN_RESNET50 | Fully Convolutional Network (FCN) semantic segmentation model with ResNet-50 backbone (21 classes, see PASCAL_VOC_LABELS). | XNNPACK, Core ML | fp16, int8 | v0.8.0 |
models.semanticSegmentation.FCN_RESNET101 | Fully Convolutional Network (FCN) semantic segmentation model with ResNet-101 backbone (21 classes, see PASCAL_VOC_LABELS). | XNNPACK, Core ML | fp16, int8 | v0.8.0 |
Pose & Keypoints
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.keypointDetection.BLAZEFACE | MediaPipe BlazeFace lightweight face detection and 6-point facial landmark locator (eyes, nose, mouth, ears, see BLAZEFACE_LANDMARKS). | XNNPACK, Vulkan | fp32, fp16 | v0.10.0 |
models.keypointDetection.FACEMESH | MediaPipe Face Mesh: a dense 468-point 3-D mesh (see FACEMESH_LANDMARKS) and a face-presence score, regressed from a 192x192 crop of one face. | XNNPACK, Core ML | fp32, fp16 | v0.11.0 |
models.keypointDetection.YOLO26_POSE | YOLO26 human pose estimation model predicting 17 COCO body keypoints (see COCO_LANDMARKS). Variants: SIZE_384, SIZE_512, SIZE_640. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.9.0 |
models.keypointDetection.RFDETR_KEYPOINT | RF-DETR (Roboflow Detection Transformer) pose keypoint detector predicting 17 COCO body keypoints (see COCO_LANDMARKS). | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.9.2 |
Depth Estimation
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.depthEstimation.DEPTH_ANYTHING_V2_SMALL | Depth Anything V2 Small with a ViT-S/14 backbone. | XNNPACK, Core ML, Vulkan | fp32, fp16, int8 | v0.11.0 |
models.depthEstimation.DEPTH_ANYTHING_V3_SMALL | Depth Anything 3 Small, exported for single-image relative depth. | XNNPACK, Core ML, Vulkan | fp32, fp16, int8 | v0.11.0 |
models.depthEstimation.ZIPDEPTH_BASE | ZipDepth Base NPU with a 384 × 384 input for low-latency depth estimation. | XNNPACK, Core ML, Vulkan | fp32, fp16 | v0.11.0 |
OCR
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.ocr.PADDLE | PP-OCRv6 small — DBNet detector plus an SVTR recognizer, one model for every language. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.10.0 |
Image Embeddings
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.imageEmbeddings.CLIP_VIT_BASE_PATCH32 | CLIP vision encoder (ViT-B/32) mapping images into a 512-dimensional shared text-image space. | XNNPACK, Core ML, MLX, Vulkan | fp16, int8 | v0.5.0 |
Image Inpainting
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.inpainting.MIGAN | MI-GAN, a mobile inpainting GAN trained on Places2 (scenes) and FFHQ (faces). Variants: SIZE_512, SIZE_256, FACES_256. | XNNPACK, Core ML, Vulkan | fp16 | v0.11.0 |
Text to Image
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.textToImage.SDXS_512_DREAMSHAPER | Ultra-fast SDXS (Stable Diffusion eXtreme Speed) 512x512 text-to-image generation model based on DreamShaper. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.10.0 |
Style Transfer
| Model | Description | Backends | Precisions | Added in |
|---|---|---|---|---|
models.styleTransfer.CANDY | Fast neural style transfer model generating a vibrant, artistic "Candy" style effect. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.2.0 |
models.styleTransfer.MOSAIC | Fast neural style transfer model applying a classic tile mosaic artistic pattern. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.2.0 |
models.styleTransfer.RAIN_PRINCESS | Fast neural style transfer model applying a painterly "Rain Princess" oil painting aesthetic. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.2.0 |
models.styleTransfer.UDNIE | Fast neural style transfer model applying Francis Picabia's "Udnie" abstract art style. | XNNPACK, Core ML, Vulkan | fp16, int8 | v0.2.0 |