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 ↗DISCOVER & COMPARE
Explore AI models 84962
Qwen3.8-27B-AWQ-W4A16-ASYM
Ar4ikov4-битный AWQ-квант Qwen/Qwen3.8-27B, сделанный llm-compressor в формате `compressed-tensors` (`pack-quantized`). Грузится в vLLM нативно. Квантование выполнено **с BF16-весов базовой модели**, а не с официального FP8-чекпоинта — чтобы не накладывать INT4 поверх уже потерянной точности. Qwen3.8-27B — гибрид: 64 слоя по схеме `16 × (3 × Gated DeltaNet → 1 × Gated Attention)`, плюс vision-башня и MTP-голова.
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗4-битный AWQ-квант orcarouter/Qwen3.8-27B-Uncensored, сделанный llm-compressor в формате `compressed-tensors` (`pack-quantized`). Грузится в vLLM нативно. Квантование выполнено **с BF16-весов**, а не поверх FP8-чекпоинта — чтобы не накладывать INT4 на уже потерянную точность. Qwen3.8-27B — гибрид: 64 слоя по схеме `16 × (3 × Gated DeltaNet → 1 × Gated Attention)`, плюс vision-башня и MTP-голова.
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 Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗multilang-pii-ner
Ar86Bat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 ↗chyon_unsloth_remerged_full_gemma_4
arabellako22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 ↗gifted_maths_unsloth_remerged_full_gemma_4
arabellako22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 ↗qwen3-asr-1.7b-ar-run3
Arabic-STT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 ↗Qwythos-9B-Claude-Mythos-5-1M-GGUF
arabsya87sy7a8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 ↗BanglaTag
arafatfahim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 ↗roberta-tiny
arampacha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。
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗whisper-large-hy-2
arampacha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。
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 ↗central-kurdish-tts
araneminiThis repository contains three **Central Kurdish (Sorani Kurdish) Text-to-Speech (TTS)** models based on the **F5-TTS** architecture. The models were developed to provide high-quality speech synthesis for a low-resource language and support applications such as speech generation, voice cloning, speech translation, and data augmentation. The models were developed within the **TTS4All initiative at the JSALT 2025 workshop**, whose objective is to facilitate the rapid development of speech synthesis systems for low-resource languages using publicly available resources. The repository includes three single-speaker F5-TTS models trained on different datasets and speaking styles.
Input Text→ Output Audio
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 Not verified→ 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 ↗calm3-22b-RP-v2-GGUF
Aratako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 ↗calm3-22b-RP-v3-GGUF
Aratako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 ↗Drama-3-Japanese
Aratako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 Audio
Price not verifiedCheck multimodal and channel pricing separately
View details ↗gemma-3-4b-it-RP-v0.1-GGUF
Aratako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 ↗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 ↗This model is the **text-only component** extracted from the Vision-Language Model mistralai/Ministral-3-8B-Base-2512. This is a weight extraction of the original VLM. For detailed benchmarks, licensing details, and architectural information, please refer to the original model card: **mistralai/Ministral-3-8B-Base-2512**
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗MioCodec-25Hz-24kHz
Aratako**MioCodec-25Hz-24kHz** is a lightweight and fast neural audio codec designed for efficient spoken language modeling. Based on the Kanade-Tokenizer implementation, this model features an integrated wave decoder (iSTFTHead) that directly synthesizes waveforms without requiring an external vocoder. For higher audio fidelity at 44.1 kHz, see MioCodec-25Hz-44.1kHz. 1. **Content Tokens:** Discrete representations that primarily capture linguistic information and phonetic content ("what" is being said) at a low frame rate (25 Hz). 2. **Global Embeddings:** A continuous vector representing broad acoustic characteristics ("how")—including speaker identity, recording environment, and microphone traits.
Input Audio→ Output Audio
Price not verifiedCheck multimodal and channel pricing separately
View details ↗MioCodec-25Hz-44.1kHz-v2
Aratako**MioCodec-25Hz-44.1kHz-v2** is an upsampled, high-fidelity version of the MioCodec-25Hz-24kHz model. By integrating an **UpsamplerBlock** inspired by Inworld TTS-1 into the decoder, this model reconstructs 44.1 kHz audio from the standard 25 Hz token stream. This model is a fine-tuned version of `MioCodec-25Hz-24kHz` with the following architectural enhancements:
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.