AI NEWS · Model intelligenceExplore capabilities. Make informed choices. ↗Profiles indexed first · Details continuously enriched
THE AI MODEL DIRECTORY Start exploring models here

Find your ideal AI model.

From language to images, open weights to APIs. Understand capabilities and compare real costs.
Find the right engine for your next idea.

Popular searches
84,938 model profiles13161 providers / publishers45 capability categories465 with comparable prices · 30 benchmarked
TText generation▧Image generation▷Video generation⌘Code generation◖Speech synthesis♫Music generation⬡3D modeling▤Document analysis
DISCOVER & COMPARE

Explore AI models 645

Discover models worth your attention

extBanglaT5

101rakibulhasan

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 ↗

GGUF conversions of `mlx-community/Hy-MT2-7B-Abliterated-bf16`, an abliterated build of Tencent's `Hy-MT2-7B` translation model. The abliteration existed only in MLX format, which means Apple Silicon and `mlx_lm` only. Every abliterated Hy-MT2 GGUF published so far is the **1.8B**; every abliterated **7B** was MLX-only. > **Modification notice** (Apache-2.0 §4(b)). These files are quantized GGUF conversions of an > abliterated derivative of `tencent/Hy-MT2-7B` — the refusal-direction ablation was performed by > mlx-community, the format > conversion here. **Neither Tencent nor the ablation author produced, endorsed, or reviewed this > repo**, and its behavior is not theirs.

Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗

small100

alirezamsh

SMaLL-100 is a compact and fast massively multilingual machine translation model covering more than 10K language pairs, that achieves competitive results with M2M-100 while being much smaller and faster. It is introduced in this paper(accepted to EMNLP2022), and initially released in this repository. The model architecture and config are the same as M2M-100 implementation, but the tokenizer is modified to adjust language codes. So, you should load the tokenizer locally from tokenization_small100.py file for the moment. Afrikaans (af), Amharic (am), Arabic (ar), Asturian (ast), Azerbaijani (az), Bashkir (ba), Belarusian (be), Bulgarian (bg), Bengali (bn), Breton (br), Bosnian (bs), Catalan; Valencian (ca), Cebuano (ceb), Czech (cs), Welsh (cy), Danish (da), German (de), Greeek (el), English (en), Spanish (es), Estonian (et), Persian (fa), Fulah (ff), Finnish (fi), French (fr), Western Frisian (fy), Irish (ga), Gaelic; Scottish Gaelic (gd), Galician (gl), Gujarati (gu), Hausa (ha), Hebrew (he), Hindi (hi), Croatian (hr), Haitian; Haitian Creole (ht), Hungarian (hu), Armenian (hy), Indonesian (id), Igbo (ig), Iloko (ilo), Icelandic (is), Italian (it), Japanese (ja), Javanese (jv), Georgian (ka), Kazakh (kk), Central Khmer (km), Kannada (kn), Korean (ko), Luxembourgish; Letzeburgesch (lb), Ganda (lg), Lingala (ln), Lao (lo), Lithuanian (lt), Latvian (lv), Malagasy (mg), Macedonian (mk), Malayalam (ml), Mongolian (mn), Marathi (mr), Malay (ms), Burmese (my), Nepali (ne), Dutch; Flemish (nl), Norwegian (no), Northern Sotho (ns), Occitan (post 1500) (oc), Oriya (or), Panjabi; Punjabi (pa), Polish (pl), Pushto; Pashto (ps), Portuguese (pt), Romanian; Moldavian; Moldovan (ro), Russian (ru), Sindhi (sd), Sinhala; Sinhalese (si), Slovak (sk), Slovenian (sl), Somali (so), Albanian (sq), Serbian (sr), Swati (ss), Sundanese (su), Swedish (sv), Swahili (sw), Tamil (ta), Thai (th), Tagalog (tl), Tswana (tn), Turkish (tr), Ukrainian (uk), Urdu (ur), Uzbek (uz), Vietnamese (vi), Wolof (wo), Xhosa (xh), Yiddish (yi), Yoruba (yo), Chinese (zh), Zulu (zu)

Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗

plt5-base

allegro

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 ↗

This repository provides three APEX quantization variants optimized for different deployment scenarios, quantized by **alphaZimuth**. Compared with the original APEX quantizations, these models were calibrated with an importance matrix (`imatrix.dat`) generated from a multilingual translation-focused calibration dataset. In practical testing, the Imatrix-calibrated versions consistently provide better translation quality and output stability compared with the non-calibrated versions.

Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗

APEX GGUF quantizations of **OS-Software/Hy-MT2-30B-A3B-uncensored-heretic**, quantized by **alphaZimuth**. This release is based directly on the existing uncensored / decensored model from **OS-Software**, rather than performing an additional uncensoring or weight-ablation process on the original Tencent model. The source model was created from **Tencent Hy-MT2-30B-A3B** using **Heretic v1.4.0+custom**, with **Arbitrary-Rank Ablation (ARA)**, a LoRA adapter, and row-norm preservation.

Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗

Aiaudio

Anthropic-ai

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 ↗
COST EXPLORER

Great models. Clear costs.

Cost analysis

Adjust monthly token usage to compare estimated API costs.

1 M = 1 million tokens · USD
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

Selection guide & FAQ
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.

AI NEWS · From information to decisions

Follow trends. Find tools. Explore models.

Explore AI news ↗Discover AI tools ↗