Intern-Decision-0.8B-GGUF
bombdefuser-124基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗DISCOVER & COMPARE
Explore AI models 84991
Intern-Decision-2B-GGUF
bombdefuser-124基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Intern-Decision-4B-GGUF
bombdefuser-124GGUF conversion of internlm/Intern-Decision-4B, a multimodal structured-decision model fine-tuned from Qwen3.5-4B. The initial language-model conversions declared 33 transformer blocks while containing 32 tensor blocks. The uploaded FP16 and Q8_0 models correct the conversion metadata to `block_count=32`, `nextn_predict_layers=0`, and 32 recurrent-layer entries. Model tensors are unchanged. This correction is required by current llama.cpp builds. Intern-Decision is a candidate-scoring model rather than a general chat model. Follow the upstream model card's decision-schema prompt format, constrain each field to its allowed single-token answer symbols, and read the candidate probabilities. The upstream calibration temperature is `1.99241824`; it was fitted on BF16 weights, so Q8_0 quantization can change calibration quality.
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Image→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗MOSS-TTS-v1.5-GGUF
bombman基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗afrolm_active_learning
bonadossou基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗meno-lite-0.1
bond005基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗meno-lite-0.1-gguf
bond005基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗ruT5-ASR-large
bond005基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗wav2vec2-large-ru-golos
bond005This model is a component of the **Pisets** speech-to-text system, presented in the paper Pisets: A Robust Speech Recognition System for Lectures and Interviews. The source code for the **Pisets** system is available on GitHub: bond005/pisets. The Wav2Vec2 model is based on facebook/wav2vec2-large-xlsr-53, fine-tuned in Russian using Sberdevices Golos with audio augmentations like as pitch shift, acceleration/deceleration of sound, reverberation etc.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗The Wav2Vec2 model is based on facebook/wav2vec2-large-xlsr-53, fine-tuned in Russian using Sberdevices Golos with audio augmentations like as pitch shift, acceleration/deceleration of sound, reverberation etc. The 2-gram language model is built on the Russian text corpus obtained from three open sources: - random 10% subset of Taiga - Russian Wikipedia - Russian Wikinews.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗whisper-large-v3-ru-podlodka
bond005基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗whisper-podlodka-turbo
bond005Whisper-Podlodka-Turbo is a new fine-tuned version of a Whisper large-v3-turbo. The main goal of the fine-tuning is to improve the quality of speech recognition and speech translation for Russian and English, as well as reduce the occurrence of hallucinations when processing non-speech audio signals. **Whisper-Podlodka-Turbo** is a new fine-tuned version of Whisper-Large-V3-Turbo, optimized for high-quality Russian speech recognition with proper punctuation + capitalization and enhanced with noise resistance capability. **Whisper-Podlodka-Turbo** is supported in Hugging Face 🤗 Transformers. To run the model, first install the Transformers library. For this example, we'll also install 🤗 Datasets to load toy audio dataset from the Hugging Face Hub, and 🤗 Accelerate to reduce the model loading time:
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Krea-2-Realism-LoRA
bonticario基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Image
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Boogu-Image-0.1-Base
Boogu基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Image
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Boogu-Image-0.1-Edit
Boogu基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Image→ Output Image
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Image
Price not verifiedCheck multimodal and channel pricing separately
View details ↗distil-ast-audioset
bookbot基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Audio→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗DistilWav2Vec2 Adult/Child Speech Classifier is an audio classification model based on the wav2vec 2.0 architecture. This model is a distilled version of wav2vec2-adult-child-cls on a private adult/child speech classification dataset. This model was trained using HuggingFace's PyTorch framework. All training was done on a Tesla P100, provided by Kaggle. Training metrics were logged via Tensorboard. Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.
Input Audio→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗gpt2-indo-small-kids-stories
bookbot基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗wav2vec2-ljspeech-gruut
bookbotWav2Vec2 LJSpeech Gruut is an automatic speech recognition model based on the wav2vec 2.0 architecture. This model is a fine-tuned version of Wav2Vec2-Base on the LJSpech Phonemes dataset. Instead of being trained to predict sequences of words, this model was trained to predict sequence of phonemes, e.g. `["h", "ɛ", "l", "ˈoʊ", "w", "ˈɚ", "l", "d"]`. Therefore, the model's vocabulary contains the different IPA phonemes found in gruut. This model was trained using HuggingFace's PyTorch framework. All training was done on a Google Cloud Engine VM with a Tesla A100 GPU. All necessary scripts used for training could be found in the Files and versions tab, as well as the Training metrics logged via Tensorboard.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Audio→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗No matching models
Adjust provider, category or input/output filters. New models are added continuously.
COST EXPLORER
Great models. Clear costs.
Adjust monthly token usage to compare estimated API costs.
1 M = 1 million tokens · USD
Compares base text-token rates within the same channel
Compares base text-token rates within the same channel
Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.
MODEL HANDBOOK
Understand before you choose
How should API prices be compared?+
Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.
Do open weights mean free commercial use?+
Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.
Is the top-ranked model the best for me?+
Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.