diff --git a/docs/source/_toctree.yml b/docs/source/_toctree.yml
index d0b622528..7abb5b9a9 100644
--- a/docs/source/_toctree.yml
+++ b/docs/source/_toctree.yml
@@ -7,6 +7,8 @@
     title: The pipeline API
   - local: custom_usage
     title: Custom usage
+  - local: good-first-models
+    title: Good-First Models
   title: Get started
 - sections:
   - local: tutorials/vanilla-js
diff --git a/docs/source/good-first-models.md b/docs/source/good-first-models.md
new file mode 100644
index 000000000..4b1b9cdd5
--- /dev/null
+++ b/docs/source/good-first-models.md
@@ -0,0 +1,735 @@
+# Recommended Transformers.js Models for First-Time Trials
+
+This guide provides curated model recommendations for each task type, selected for their:
+- **Popularity**: Widely used with strong community support
+- **Performance**: Fast loading and inference times
+- **WebGPU Compatibility**: GPU-accelerated in modern browsers
+
+**Important:** These recommendations are designed for initial experimentation and learning. Many other models are available for each task. **You should evaluate and choose the best model for your specific use case, performance requirements, and constraints.**
+
+## About the Model Recommendations
+
+The models below are selected for their popularity and ease of use, making them ideal for initial experimentation. **This list does not cover all available models** - you should evaluate and select the best model for your specific use case and requirements.
+
+## Audio-Classification
+
+**Usage Example:** Perform audio classification
+
+```javascript
+const classifier = await pipeline('audio-classification', 'onnx-community/Musical-genres-Classification-Hubert-V1-ONNX');
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
+const output = await classifier(url);
+```
+
+### Recommended Models for First-Time Trials
+
+#### onnx-community/Musical-genres-Classification-Hubert-V1-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/Musical-genres-Classification-Hubert-V1-ONNX](https://huggingface.co/onnx-community/Musical-genres-Classification-Hubert-V1-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 264.4ms | Inference: 136.5ms
+
+#### Xenova/ast-finetuned-audioset-10-10-0.4593
+
+- **Model page:** [https://huggingface.co/Xenova/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/Xenova/ast-finetuned-audioset-10-10-0.4593)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 2827.1ms | Inference: 544.1ms
+
+#### Xenova/ast-finetuned-speech-commands-v2
+
+- **Model page:** [https://huggingface.co/Xenova/ast-finetuned-speech-commands-v2](https://huggingface.co/Xenova/ast-finetuned-speech-commands-v2)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 3254.1ms | Inference: 759.0ms
+
+#### onnx-community/Speech-Emotion-Classification-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/Speech-Emotion-Classification-ONNX](https://huggingface.co/onnx-community/Speech-Emotion-Classification-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 3070.4ms | Inference: 574.9ms
+
+#### Xenova/wav2vec2-base-superb-ks
+
+- **Model page:** [https://huggingface.co/Xenova/wav2vec2-base-superb-ks](https://huggingface.co/Xenova/wav2vec2-base-superb-ks)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 3211.4ms | Inference: 584.7ms
+
+---
+
+## Automatic-Speech-Recognition
+
+**Usage Example:** Transcribe audio from a URL
+
+```javascript
+const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny.en');
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
+const output = await transcriber(url);
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/whisper-tiny.en
+
+- **Model page:** [https://huggingface.co/Xenova/whisper-tiny.en](https://huggingface.co/Xenova/whisper-tiny.en)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1045.6ms | Inference: 1314.3ms
+
+#### Xenova/whisper-tiny
+
+- **Model page:** [https://huggingface.co/Xenova/whisper-tiny](https://huggingface.co/Xenova/whisper-tiny)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1037.2ms | Inference: 1258.4ms
+
+#### onnx-community/moonshine-base-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/moonshine-base-ONNX](https://huggingface.co/onnx-community/moonshine-base-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1906.3ms | Inference: 889.1ms
+
+#### onnx-community/whisper-base
+
+- **Model page:** [https://huggingface.co/onnx-community/whisper-base](https://huggingface.co/onnx-community/whisper-base)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1885.8ms | Inference: 878.9ms
+
+#### Xenova/whisper-base.en
+
+- **Model page:** [https://huggingface.co/Xenova/whisper-base.en](https://huggingface.co/Xenova/whisper-base.en)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1591.3ms | Inference: 1941.5ms
+
+---
+
+## Depth-Estimation
+
+**Usage Example:** Depth estimation
+
+```javascript
+const depth_estimator = await pipeline('depth-estimation', 'Xenova/depth-anything-small-hf');
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';
+const out = await depth_estimator(url);
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/depth-anything-small-hf
+
+- **Model page:** [https://huggingface.co/Xenova/depth-anything-small-hf](https://huggingface.co/Xenova/depth-anything-small-hf)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 414.3ms | Inference: 419.3ms
+
+#### onnx-community/depth-anything-v2-small
+
+- **Model page:** [https://huggingface.co/onnx-community/depth-anything-v2-small](https://huggingface.co/onnx-community/depth-anything-v2-small)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 450.0ms | Inference: 357.1ms
+
+#### onnx-community/metric3d-vit-small
+
+- **Model page:** [https://huggingface.co/onnx-community/metric3d-vit-small](https://huggingface.co/onnx-community/metric3d-vit-small)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 786.2ms | Inference: 515.7ms
+
+#### Xenova/glpn-nyu
+
+- **Model page:** [https://huggingface.co/Xenova/glpn-nyu](https://huggingface.co/Xenova/glpn-nyu)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1454.5ms | Inference: 1076.9ms
+
+#### Xenova/glpn-kitti
+
+- **Model page:** [https://huggingface.co/Xenova/glpn-kitti](https://huggingface.co/Xenova/glpn-kitti)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1451.4ms | Inference: 1083.3ms
+
+---
+
+## Feature-Extraction
+
+**Usage Example:** Run feature extraction
+
+```javascript
+const extractor = await pipeline('feature-extraction', 'Xenova/all-MiniLM-L6-v2');
+const output = await extractor('This is a simple test.');
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/all-MiniLM-L6-v2
+
+- **Model page:** [https://huggingface.co/Xenova/all-MiniLM-L6-v2](https://huggingface.co/Xenova/all-MiniLM-L6-v2)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 373.5ms | Inference: 143.9ms
+
+#### Xenova/bge-base-en-v1.5
+
+- **Model page:** [https://huggingface.co/Xenova/bge-base-en-v1.5](https://huggingface.co/Xenova/bge-base-en-v1.5)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 3620.8ms | Inference: 816.4ms
+
+#### Xenova/gte-small
+
+- **Model page:** [https://huggingface.co/Xenova/gte-small](https://huggingface.co/Xenova/gte-small)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 588.7ms | Inference: 228.4ms
+
+#### onnx-community/bert_uncased_L-2_H-128_A-2-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/bert_uncased_L-2_H-128_A-2-ONNX](https://huggingface.co/onnx-community/bert_uncased_L-2_H-128_A-2-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 110.8ms | Inference: 49.2ms
+
+#### Xenova/paraphrase-albert-base-v2
+
+- **Model page:** [https://huggingface.co/Xenova/paraphrase-albert-base-v2](https://huggingface.co/Xenova/paraphrase-albert-base-v2)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 328.8ms | Inference: 39.1ms
+
+---
+
+## Fill-Mask
+
+**Usage Example:** Perform masked language modelling (a.k.a. "fill-mask")
+
+```javascript
+const unmasker = await pipeline('fill-mask', 'Xenova/distilbert-base-uncased');
+const output = await unmasker('The goal of life is [MASK].');
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/distilbert-base-uncased
+
+- **Model page:** [https://huggingface.co/Xenova/distilbert-base-uncased](https://huggingface.co/Xenova/distilbert-base-uncased)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 769.8ms | Inference: 302.4ms
+
+#### Xenova/bert-base-uncased
+
+- **Model page:** [https://huggingface.co/Xenova/bert-base-uncased](https://huggingface.co/Xenova/bert-base-uncased)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 4432.7ms | Inference: 919.4ms
+
+#### Xenova/albert-base-v2
+
+- **Model page:** [https://huggingface.co/Xenova/albert-base-v2](https://huggingface.co/Xenova/albert-base-v2)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 324.9ms | Inference: 68.1ms
+
+#### Xenova/distilbert-base-cased
+
+- **Model page:** [https://huggingface.co/Xenova/distilbert-base-cased](https://huggingface.co/Xenova/distilbert-base-cased)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 742.7ms | Inference: 301.1ms
+
+#### Xenova/albert-large-v2
+
+- **Model page:** [https://huggingface.co/Xenova/albert-large-v2](https://huggingface.co/Xenova/albert-large-v2)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 499.6ms | Inference: 78.8ms
+
+---
+
+## Image-Classification
+
+**Usage Example:** Classify an image
+
+```javascript
+const classifier = await pipeline('image-classification', 'Xenova/vit-base-patch16-224');
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg';
+const output = await classifier(url);
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/vit-base-patch16-224
+
+- **Model page:** [https://huggingface.co/Xenova/vit-base-patch16-224](https://huggingface.co/Xenova/vit-base-patch16-224)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 2894.1ms | Inference: 476.3ms
+
+#### Xenova/facial_emotions_image_detection
+
+- **Model page:** [https://huggingface.co/Xenova/facial_emotions_image_detection](https://huggingface.co/Xenova/facial_emotions_image_detection)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 2922.3ms | Inference: 479.3ms
+
+#### Xenova/resnet-18
+
+- **Model page:** [https://huggingface.co/Xenova/resnet-18](https://huggingface.co/Xenova/resnet-18)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 152.1ms | Inference: 90.8ms
+
+#### Xenova/resnet-50
+
+- **Model page:** [https://huggingface.co/Xenova/resnet-50](https://huggingface.co/Xenova/resnet-50)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 304.9ms | Inference: 160.5ms
+
+#### onnx-community/mobilenet_v2_1.0_224
+
+- **Model page:** [https://huggingface.co/onnx-community/mobilenet_v2_1.0_224](https://huggingface.co/onnx-community/mobilenet_v2_1.0_224)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 90.7ms | Inference: 99.7ms
+
+---
+
+## Image-Feature-Extraction
+
+**Usage Example:** Perform image feature extraction
+
+```javascript
+const image_feature_extractor = await pipeline('image-feature-extraction', 'onnx-community/dinov3-vits16-pretrain-lvd1689m-ONNX');
+const url = 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cats.png';
+const features = await image_feature_extractor(url);
+```
+
+### Recommended Models for First-Time Trials
+
+#### onnx-community/dinov3-vits16-pretrain-lvd1689m-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/dinov3-vits16-pretrain-lvd1689m-ONNX](https://huggingface.co/onnx-community/dinov3-vits16-pretrain-lvd1689m-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 311.4ms | Inference: 352.4ms
+
+#### Xenova/dino-vits16
+
+- **Model page:** [https://huggingface.co/Xenova/dino-vits16](https://huggingface.co/Xenova/dino-vits16)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 321.7ms | Inference: 247.3ms
+
+#### onnx-community/dinov3-vits16-pretrain-lvd1689m-ONNX-MHA-scores
+
+- **Model page:** [https://huggingface.co/onnx-community/dinov3-vits16-pretrain-lvd1689m-ONNX-MHA-scores](https://huggingface.co/onnx-community/dinov3-vits16-pretrain-lvd1689m-ONNX-MHA-scores)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 342.8ms | Inference: 259.6ms
+
+#### onnx-community/dinov2-small-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/dinov2-small-ONNX](https://huggingface.co/onnx-community/dinov2-small-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 311.5ms | Inference: 264.2ms
+
+#### onnx-community/dinov2-with-registers-small
+
+- **Model page:** [https://huggingface.co/onnx-community/dinov2-with-registers-small](https://huggingface.co/onnx-community/dinov2-with-registers-small)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 312.4ms | Inference: 270.6ms
+
+---
+
+## Image-Segmentation
+
+**Usage Example:** Perform image segmentation
+
+```javascript
+const segmenter = await pipeline('image-segmentation', 'Xenova/segformer-b0-finetuned-ade-512-512');
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';
+const output = await segmenter(url);
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/segformer-b0-finetuned-ade-512-512
+
+- **Model page:** [https://huggingface.co/Xenova/segformer-b0-finetuned-ade-512-512](https://huggingface.co/Xenova/segformer-b0-finetuned-ade-512-512)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 205.6ms | Inference: 1612.3ms
+
+#### Xenova/modnet
+
+- **Model page:** [https://huggingface.co/Xenova/modnet](https://huggingface.co/Xenova/modnet)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 144.6ms | Inference: 286.9ms
+
+#### onnx-community/modnet-webnn
+
+- **Model page:** [https://huggingface.co/onnx-community/modnet-webnn](https://huggingface.co/onnx-community/modnet-webnn)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 147.5ms | Inference: 223.2ms
+
+#### Xenova/segformer_b0_clothes
+
+- **Model page:** [https://huggingface.co/Xenova/segformer_b0_clothes](https://huggingface.co/Xenova/segformer_b0_clothes)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 203.9ms | Inference: 632.4ms
+
+#### Xenova/segformer-b0-finetuned-cityscapes-1024-1024
+
+- **Model page:** [https://huggingface.co/Xenova/segformer-b0-finetuned-cityscapes-1024-1024](https://huggingface.co/Xenova/segformer-b0-finetuned-cityscapes-1024-1024)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 200.2ms | Inference: 519.0ms
+
+---
+
+## Image-To-Image
+
+**Usage Example:**
+
+```javascript
+const processor = await pipeline('image-to-image', 'Xenova/2x_APISR_RRDB_GAN_generator-onnx');
+const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg';
+const output = await processor(url);
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/2x_APISR_RRDB_GAN_generator-onnx
+
+- **Model page:** [https://huggingface.co/Xenova/2x_APISR_RRDB_GAN_generator-onnx](https://huggingface.co/Xenova/2x_APISR_RRDB_GAN_generator-onnx)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 117.5ms | Inference: 596.3ms
+
+#### Xenova/4x_APISR_GRL_GAN_generator-onnx
+
+- **Model page:** [https://huggingface.co/Xenova/4x_APISR_GRL_GAN_generator-onnx](https://huggingface.co/Xenova/4x_APISR_GRL_GAN_generator-onnx)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 2712.5ms | Inference: 3362.6ms
+
+---
+
+## Object-Detection
+
+**Usage Example:** Run object-detection
+
+```javascript
+const detector = await pipeline('object-detection', 'Xenova/detr-resnet-50');
+const img = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/cats.jpg';
+const output = await detector(img, { threshold: 0.9 });
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/detr-resnet-50
+
+- **Model page:** [https://huggingface.co/Xenova/detr-resnet-50](https://huggingface.co/Xenova/detr-resnet-50)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 718.2ms | Inference: 625.4ms
+
+#### Xenova/yolos-tiny
+
+- **Model page:** [https://huggingface.co/Xenova/yolos-tiny](https://huggingface.co/Xenova/yolos-tiny)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 190.1ms | Inference: 904.3ms
+
+#### onnx-community/rfdetr_base-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/rfdetr_base-ONNX](https://huggingface.co/onnx-community/rfdetr_base-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 470.4ms | Inference: 420.9ms
+
+#### Xenova/yolos-small-300
+
+- **Model page:** [https://huggingface.co/Xenova/yolos-small-300](https://huggingface.co/Xenova/yolos-small-300)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 400.0ms | Inference: 1776.1ms
+
+#### onnx-community/rfdetr_medium-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/rfdetr_medium-ONNX](https://huggingface.co/onnx-community/rfdetr_medium-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 578.1ms | Inference: 486.1ms
+
+---
+
+## Question-Answering
+
+**Usage Example:** Run question answering
+
+```javascript
+const answerer = await pipeline('question-answering', 'Xenova/distilbert-base-cased-distilled-squad');
+const question = 'Who was Jim Henson?';
+const context = 'Jim Henson was a nice puppet.';
+const output = await answerer(question, context);
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/distilbert-base-cased-distilled-squad
+
+- **Model page:** [https://huggingface.co/Xenova/distilbert-base-cased-distilled-squad](https://huggingface.co/Xenova/distilbert-base-cased-distilled-squad)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 746.8ms | Inference: 164.3ms
+
+#### onnx-community/rubert_tiny_qa_kontur-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/rubert_tiny_qa_kontur-ONNX](https://huggingface.co/onnx-community/rubert_tiny_qa_kontur-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 411.4ms | Inference: 111.1ms
+
+#### Xenova/distilbert-base-uncased-distilled-squad
+
+- **Model page:** [https://huggingface.co/Xenova/distilbert-base-uncased-distilled-squad](https://huggingface.co/Xenova/distilbert-base-uncased-distilled-squad)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 726.1ms | Inference: 204.5ms
+
+#### onnx-community/xlm-roberta-base-squad2-distilled-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/xlm-roberta-base-squad2-distilled-ONNX](https://huggingface.co/onnx-community/xlm-roberta-base-squad2-distilled-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 9046.6ms | Inference: 1201.1ms
+
+#### onnx-community/mobilebert-uncased-squad-v2-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/mobilebert-uncased-squad-v2-ONNX](https://huggingface.co/onnx-community/mobilebert-uncased-squad-v2-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 465.3ms | Inference: 911.1ms
+
+---
+
+## Summarization
+
+**Usage Example:** Summarization
+
+```javascript
+const generator = await pipeline('summarization', 'Xenova/distilbart-cnn-6-6');
+const text = 'The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, ' +
+  'and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. ' +
+  'During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest ' +
+  'man-made structure in the world, a title it held for 41 years until the Chrysler Building in New ' +
+  'York City was finished in 1930. It was the first structure to reach a height of 300 metres. Due to ' +
+  'the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the ' +
+  'Chrysler Building by 5.2 metres (17 ft). Excluding transmitters, the Eiffel Tower is the second ' +
+  'tallest free-standing structure in France after the Millau Viaduct.';
+const output = await generator(text, {
+  max_new_tokens: 100,
+});
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/distilbart-cnn-6-6
+
+- **Model page:** [https://huggingface.co/Xenova/distilbart-cnn-6-6](https://huggingface.co/Xenova/distilbart-cnn-6-6)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 9311.4ms | Inference: 2527.9ms
+
+#### Xenova/distilbart-xsum-12-1
+
+- **Model page:** [https://huggingface.co/Xenova/distilbart-xsum-12-1](https://huggingface.co/Xenova/distilbart-xsum-12-1)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 8184.2ms | Inference: 1283.7ms
+
+#### Xenova/distilbart-xsum-6-6
+
+- **Model page:** [https://huggingface.co/Xenova/distilbart-xsum-6-6](https://huggingface.co/Xenova/distilbart-xsum-6-6)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 8895.0ms | Inference: 1519.4ms
+
+#### Xenova/distilbart-xsum-9-6
+
+- **Model page:** [https://huggingface.co/Xenova/distilbart-xsum-9-6](https://huggingface.co/Xenova/distilbart-xsum-9-6)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 10079.9ms | Inference: 1730.8ms
+
+#### Xenova/distilbart-cnn-12-3
+
+- **Model page:** [https://huggingface.co/Xenova/distilbart-cnn-12-3](https://huggingface.co/Xenova/distilbart-cnn-12-3)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 8878.6ms | Inference: 2479.6ms
+
+---
+
+## Text-Classification
+
+**Usage Example:**
+
+```javascript
+const classifier = await pipeline('text-classification', 'Xenova/distilbert-base-uncased-finetuned-sst-2-english');
+const output = await classifier('I love transformers!');
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/distilbert-base-uncased-finetuned-sst-2-english
+
+- **Model page:** [https://huggingface.co/Xenova/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/Xenova/distilbert-base-uncased-finetuned-sst-2-english)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 662.4ms | Inference: 245.3ms
+
+#### Xenova/ms-marco-MiniLM-L-6-v2
+
+- **Model page:** [https://huggingface.co/Xenova/ms-marco-MiniLM-L-6-v2](https://huggingface.co/Xenova/ms-marco-MiniLM-L-6-v2)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 365.1ms | Inference: 146.6ms
+
+#### Xenova/ms-marco-TinyBERT-L-2-v2
+
+- **Model page:** [https://huggingface.co/Xenova/ms-marco-TinyBERT-L-2-v2](https://huggingface.co/Xenova/ms-marco-TinyBERT-L-2-v2)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 115.1ms | Inference: 56.2ms
+
+#### Xenova/toxic-bert
+
+- **Model page:** [https://huggingface.co/Xenova/toxic-bert](https://huggingface.co/Xenova/toxic-bert)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 3789.0ms | Inference: 808.8ms
+
+#### onnx-community/language_detection-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/language_detection-ONNX](https://huggingface.co/onnx-community/language_detection-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 338.1ms | Inference: 116.0ms
+
+---
+
+## Text-Generation
+
+**Usage Example:** Text generation
+
+```javascript
+const generator = await pipeline('text-generation', 'Xenova/distilgpt2');
+const output = await generator('Once upon a time, there was', { max_new_tokens: 10 });
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/distilgpt2
+
+- **Model page:** [https://huggingface.co/Xenova/distilgpt2](https://huggingface.co/Xenova/distilgpt2)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 3207.5ms | Inference: 469.7ms
+
+#### Xenova/llama2.c-stories15M
+
+- **Model page:** [https://huggingface.co/Xenova/llama2.c-stories15M](https://huggingface.co/Xenova/llama2.c-stories15M)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 396.8ms | Inference: 251.4ms
+
+#### onnx-community/ettin-decoder-17m-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/ettin-decoder-17m-ONNX](https://huggingface.co/onnx-community/ettin-decoder-17m-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 328.2ms | Inference: 221.9ms
+
+#### onnx-community/Lamina-extend-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/Lamina-extend-ONNX](https://huggingface.co/onnx-community/Lamina-extend-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 141.9ms | Inference: 190.0ms
+
+#### onnx-community/chess-llama-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/chess-llama-ONNX](https://huggingface.co/onnx-community/chess-llama-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 249.3ms | Inference: 197.2ms
+
+---
+
+## Token-Classification
+
+**Usage Example:** Perform named entity recognition
+
+```javascript
+const classifier = await pipeline('token-classification', 'onnx-community/NeuroBERT-NER-ONNX');
+const output = await classifier('My name is Sarah and I live in London');
+```
+
+### Recommended Models for First-Time Trials
+
+#### onnx-community/NeuroBERT-NER-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/NeuroBERT-NER-ONNX](https://huggingface.co/onnx-community/NeuroBERT-NER-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 170.4ms | Inference: 61.6ms
+
+#### onnx-community/TinyBERT-finetuned-NER-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/TinyBERT-finetuned-NER-ONNX](https://huggingface.co/onnx-community/TinyBERT-finetuned-NER-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 261.7ms | Inference: 79.9ms
+
+#### Xenova/esm2_t6_8M_UR50D_rna_binding_site_predictor
+
+- **Model page:** [https://huggingface.co/Xenova/esm2_t6_8M_UR50D_rna_binding_site_predictor](https://huggingface.co/Xenova/esm2_t6_8M_UR50D_rna_binding_site_predictor)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 279.3ms | Inference: 118.6ms
+
+#### onnx-community/distilbert-NER-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/distilbert-NER-ONNX](https://huggingface.co/onnx-community/distilbert-NER-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 682.0ms | Inference: 258.2ms
+
+#### onnx-community/small-e-czech-finetuned-ner-wikiann-ONNX
+
+- **Model page:** [https://huggingface.co/onnx-community/small-e-czech-finetuned-ner-wikiann-ONNX](https://huggingface.co/onnx-community/small-e-czech-finetuned-ner-wikiann-ONNX)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 271.3ms | Inference: 193.4ms
+
+---
+
+## Translation
+
+**Usage Example:** Multilingual translation
+
+```javascript
+const translator = await pipeline('translation', 'Xenova/opus-mt-en-es');
+const output = await translator('Life is like a box of chocolate.', {
+  src_lang: '...',
+  tgt_lang: '...',
+});
+```
+
+### Recommended Models for First-Time Trials
+
+#### Xenova/opus-mt-en-es
+
+- **Model page:** [https://huggingface.co/Xenova/opus-mt-en-es](https://huggingface.co/Xenova/opus-mt-en-es)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1956.5ms | Inference: 617.7ms
+
+#### Xenova/opus-mt-zh-en
+
+- **Model page:** [https://huggingface.co/Xenova/opus-mt-zh-en](https://huggingface.co/Xenova/opus-mt-zh-en)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1964.7ms | Inference: 799.0ms
+
+#### Xenova/opus-mt-en-zh
+
+- **Model page:** [https://huggingface.co/Xenova/opus-mt-en-zh](https://huggingface.co/Xenova/opus-mt-en-zh)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1830.0ms | Inference: 481.5ms
+
+#### Xenova/opus-mt-en-fr
+
+- **Model page:** [https://huggingface.co/Xenova/opus-mt-en-fr](https://huggingface.co/Xenova/opus-mt-en-fr)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1786.1ms | Inference: 446.7ms
+
+#### Xenova/opus-mt-ar-en
+
+- **Model page:** [https://huggingface.co/Xenova/opus-mt-ar-en](https://huggingface.co/Xenova/opus-mt-ar-en)
+- **WebGPU Compatible:** ✅ Yes
+- **Metrics:** Load: 1756.6ms | Inference: 733.8ms
+
+---
+
+## About These Recommendations
+
+### Selection Criteria
+
+Models in this guide are selected based on:
+- **Popularity**: High download counts and community engagement on HuggingFace Hub
+- **Performance**: Fast loading and inference times based on benchmark results
+- **Compatibility**: Verified WebGPU support for GPU-accelerated browser execution
+
+### Understanding Benchmark Metrics
+
+**Important:** All performance metrics (load time, inference time, etc.) are measured in a controlled benchmark environment. These metrics are useful for **comparing models against each other**, but they may not reflect the actual performance you'll experience in your specific environment. Factors that affect real-world performance include:
+- Hardware specifications (CPU, GPU, memory)
+- Browser type and version
+- Operating system
+- Network conditions (for model loading)
+- Concurrent processes and system load
+
+**We recommend** benchmarking models in your own environment with your actual use case to get accurate performance measurements.
+
+### For Production Use
+
+These recommendations are optimized for first-time trials and learning. For production applications, consider:
+- Evaluating multiple models for your specific use case
+- Testing with your actual data and performance requirements
+- Reviewing the full benchmark results for comprehensive comparisons
+- Exploring specialized models that may better fit your needs
+
+Visit the full leaderboard to explore all available models and their benchmark results.
diff --git a/src/pipelines.js b/src/pipelines.js
index 6c84403e2..a44efbb25 100644
--- a/src/pipelines.js
+++ b/src/pipelines.js
@@ -268,6 +268,9 @@ export class Pipeline extends Callable {
  * //   { label: 'severe_toxic', score: 0.005651099607348442 }
  * // ]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#text-classification)
  */
 export class TextClassificationPipeline extends (/** @type {new (options: TextPipelineConstructorArgs) => TextClassificationPipelineType} */ (Pipeline)) {
 
@@ -379,6 +382,9 @@ export class TextClassificationPipeline extends (/** @type {new (options: TextPi
  * //   { entity: 'I-LOC', score: 0.9975294470787048, index: 8, word: 'America' }
  * // ]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#token-classification)
  */
 export class TokenClassificationPipeline extends (/** @type {new (options: TextPipelineConstructorArgs) => TokenClassificationPipelineType} */ (Pipeline)) {
 
@@ -486,6 +492,9 @@ export class TokenClassificationPipeline extends (/** @type {new (options: TextP
  * //   score: 0.5768911502526741
  * // }
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#question-answering)
  */
 export class QuestionAnsweringPipeline extends (/** @type {new (options: TextPipelineConstructorArgs) => QuestionAnsweringPipelineType} */ (Pipeline)) {
 
@@ -636,6 +645,9 @@ export class QuestionAnsweringPipeline extends (/** @type {new (options: TextPip
  * const output = await unmasker('The Milky Way is a [MASK] galaxy.', { top_k: 1 });
  * // [{ token_str: 'spiral', score: 0.6299987435340881, token: 14061, sequence: 'The Milky Way is a spiral galaxy.' }]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#fill-mask)
  */
 export class FillMaskPipeline extends (/** @type {new (options: TextPipelineConstructorArgs) => FillMaskPipelineType} */ (Pipeline)) {
 
@@ -821,6 +833,9 @@ export class Text2TextGenerationPipeline extends (/** @type {new (options: TextP
  * });
  * // [{ summary_text: ' The Eiffel Tower is about the same height as an 81-storey building and the tallest structure in Paris. It is the second tallest free-standing structure in France after the Millau Viaduct.' }]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#summarization)
  */
 export class SummarizationPipeline extends (/** @type {new (options: TextPipelineConstructorArgs) => SummarizationPipelineType} */ (/** @type {any} */ (Text2TextGenerationPipeline))) {
     /** @type {'summary_text'} */
@@ -893,6 +908,9 @@ export class SummarizationPipeline extends (/** @type {new (options: TextPipelin
  * });
  * // [{ translation_text: 'Le chef des Nations affirme qu 'il n 'y a military solution in Syria.' }]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#translation)
  */
 export class TranslationPipeline extends (/** @type {new (options: TextPipelineConstructorArgs) => TranslationPipelineType} */ (/** @type {any} */ (Text2TextGenerationPipeline))) {
     /** @type {'translation_text'} */
@@ -980,6 +998,9 @@ function isChat(x) {
  * //     '        return fib(n-1) + fib(n-2)\n'
  * // }]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#text-generation)
  */
 export class TextGenerationPipeline extends (/** @type {new (options: TextPipelineConstructorArgs) => TextGenerationPipelineType} */ (Pipeline)) {
 
@@ -1291,6 +1312,9 @@ export class ZeroShotClassificationPipeline extends (/** @type {new (options: Te
  * //   dims: [1, 48]
  * // }
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#feature-extraction)
  */
 export class FeatureExtractionPipeline extends (/** @type {new (options: TextPipelineConstructorArgs) => FeatureExtractionPipelineType} */ (Pipeline)) {
     /**
@@ -1399,6 +1423,9 @@ export class FeatureExtractionPipeline extends (/** @type {new (options: TextPip
  * //   size: 512
  * // }
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#image-feature-extraction)
  */
 export class ImageFeatureExtractionPipeline extends (/** @type {new (options: ImagePipelineConstructorArgs) => ImageFeatureExtractionPipelineType} */ (Pipeline)) {
     /**
@@ -1487,6 +1514,9 @@ export class ImageFeatureExtractionPipeline extends (/** @type {new (options: Im
  * //   { label: 'Animal', score: 0.08985692262649536 },
  * // ]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#audio-classification)
  */
 export class AudioClassificationPipeline extends (/** @type {new (options: AudioPipelineConstructorArgs) => AudioClassificationPipelineType} */ (Pipeline)) {
 
@@ -1728,6 +1758,9 @@ export class ZeroShotAudioClassificationPipeline extends (/** @type {new (option
  * const output = await transcriber(url, { chunk_length_s: 30, stride_length_s: 5 });
  * // { text: " So in college, I was a government major, which means [...] So I'd start off light and I'd bump it up" }
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#automatic-speech-recognition)
  */
 export class AutomaticSpeechRecognitionPipeline extends (/** @type {new (options: TextAudioPipelineConstructorArgs) => AutomaticSpeechRecognitionPipelineType} */ (Pipeline)) {
 
@@ -2060,6 +2093,9 @@ export class ImageToTextPipeline extends (/** @type {new (options: TextImagePipe
  * //   ...
  * // ]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#image-classification)
  */
 export class ImageClassificationPipeline extends (/** @type {new (options: ImagePipelineConstructorArgs) => ImageClassificationPipelineType} */ (Pipeline)) {
 
@@ -2145,6 +2181,9 @@ export class ImageClassificationPipeline extends (/** @type {new (options: Image
  * //   { label: 'cat', score: 0.9994316101074219, mask: RawImage { ... } }
  * // ]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#image-segmentation)
  */
 export class ImageSegmentationPipeline extends (/** @type {new (options: ImagePipelineConstructorArgs) => ImageSegmentationPipelineType} */ (Pipeline)) {
     /**
@@ -2484,6 +2523,9 @@ export class ZeroShotImageClassificationPipeline extends (/** @type {new (option
  * //   box: { xmin: 331, ymin: 19, xmax: 649, ymax: 371 }
  * // }]
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#object-detection)
  */
 export class ObjectDetectionPipeline extends (/** @type {new (options: ImagePipelineConstructorArgs) => ObjectDetectionPipelineType} */ (Pipeline)) {
 
@@ -2950,6 +2992,9 @@ export class TextToAudioPipeline extends (/** @type {new (options: TextToAudioPi
  * //   channels: 3
  * // }
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#image-to-image)
  */
 export class ImageToImagePipeline extends (/** @type {new (options: ImagePipelineConstructorArgs) => ImageToImagePipelineType} */ (Pipeline)) {
     /**
@@ -3013,6 +3058,9 @@ export class ImageToImagePipeline extends (/** @type {new (options: ImagePipelin
  * //   }
  * // }
  * ```
+ *
+ * ### Quickstart models
+ * See [Quickstart models](../good-first-models#depth-estimation)
  */
 export class DepthEstimationPipeline extends (/** @type {new (options: ImagePipelineConstructorArgs) => DepthEstimationPipelineType} */ (Pipeline)) {
     /**