Free AI for Open Source

A grant of 15,000,000 free AI tokens plus Pro-tier API access for maintainers of actively maintained open source projects.

Àwọn ìṣàmúlò-ètò AI

Àwọn àwọn ìṣàmúlò-ètò àwọn ìṣàmúlò-ètò gbogbo ní pàtó Free.ai ní ìṣàmúlò-ètò ìṣísẹ̀ láti ìsàlẹ̀-ètò àìfàyé (Apache 2.0, MIT, BSD). Kò ní àwọn ìsàlẹ̀-ètò Llama/Meta. À ń ró pé AI láti jẹ́ àìfàyé, àìṣàmúlò-ètò, àti àìfẹ́ láti lo.

Chat Àwọn ìṣàmúlò-ètò Àwọn

Àwọn ìṣàmúlò-ètò	Àwọn Ìṣàmúlò-ètò	Àwọn Àmì-ìwé	Àwọn Ìṣàmúlò-ètò
Qwen2.5-72B	Ìgbàkọ́ ìpele, ìṣàfarawé, ìṣàfarawé	_Ìṣàmúlò-ètò	HuggingFace
Qwen2.5-7B	Àwọn àkọlé àìpẹ́, àwọn iṣẹ́ àìpẹ́	_Ìṣàmúlò-ètò	HuggingFace
Mistral-7B	Àwọn àkọlé àìpẹ́, àwọn ìṣàmúlò-ètò ìpele	_Ìṣàmúlò-ètò	HuggingFace
Phi-3	Ìṣàmúlò-ètò, àwọn mátírika	MIT	HuggingFace

Àwọn ìṣàmúlò-ètò

Àwọn ìṣàmúlò-ètò	Àwọn Ìṣàmúlò-ètò	Àwọn Àmì-ìwé	Àwọn Ìṣàmúlò-ètò
Qwen2.5-Coder-32B	Ìṣàfilọ́lẹ̀ àwọn àmì-ìwé, ìṣàmúlò-ètò	_Ìṣàmúlò-ètò	HuggingFace
DeepSeek-Coder-V2-Lite	Ìṣàmúlò-ètò ìṣàfarawé àwọn àkóónú	MIT	HuggingFace

Àwọn ìṣàmúlò-ètò àwòrán

Àwọn ìṣàmúlò-ètò	Àwọn Ìṣàmúlò-ètò	Àwọn Àmì-ìwé	Àwọn Ìṣàmúlò-ètò
_Ìjáde	Àwọn àwòrán	_Ìṣàmúlò-ètò	HuggingFace
Stable Diffusion XL	Àwọn ààtò àwòrán	OpenRAIL++	HuggingFace
_Ìṣàmúlò-ètò	Àwọn àwòrán àwọn àwọn àwòrán	_Ìṣàmúlò-ètò	HuggingFace
_Ìṣàmúlò-ètò	Ìṣàfilọ́lẹ̀ àwọn ààyè-iṣẹ́ láti inú àkọ́lé	_Ìṣàmúlò-ètò	HuggingFace

Àwọn ìṣàmúlò-ètò Àkọ́kọ́

Àwọn ìṣàmúlò-ètò	Àwọn Ìṣàmúlò-ètò	Àwọn Àmì-ìwé	Àwọn Ìṣàmúlò-ètò
_Ìṣàmúlò-ètò	Àkọ́lé-si-Ìrọ̀gbèsì	_Ìṣàmúlò-ètò	HuggingFace
_Ìṣàmúlò-ètò	Àkọ́lé-si-Ìrọ̀gbèsì	MIT	GitHub
_Ìṣàmúlò-ètò	Àkọ́lé-si-Ìrọ̀gbèsì	MIT	GitHub
_Ìṣàmúlò-ètò	Àkọ́lé-si-Ìrọ̀gbèsì	MIT	HuggingFace
Àwọn Ìjánu-ìsún	Àkọ́lé-si-Ìrọ̀gbèsì	_Ìṣàmúlò-ètò	HuggingFace
_Ìṣàmúlò-ètò	Àwọn Àkọ́lé	MIT	GitHub
Àwọn àwọn àyọkà ìṣàmúlò-ètò	Àwọn Àkọ́lé	_Ìṣàmúlò-ètò	GitHub
ACE-Step 3.5B	Ìṣàfilọ́lẹ̀ ìṣàmúlò-ètò	_Ìṣàmúlò-ètò	HuggingFace
Mel-Band RoFormer	Ìdàràn àwọn ìṣàfarawé àwọn ìtàn (àwọn àkọ́lé, àwọn ìṣàmúlò-ètò)	MIT	arXiv
SCNet	Ìdáràn àwọn ìṣàfarawé àwọn ìtàn (àti àwọn àkọ́lé)	_Ìṣàmúlò-ètò	arXiv

Àwọn ìṣàfarawé, àwọn ìṣàmúlò-ètò àti àwọn àwọn ìṣàmúlò-ètò mìíràn

Àwọn ìṣàmúlò-ètò	Àwọn Ìṣàmúlò-ètò	Àwọn Àmì-ìwé	Àwọn Ìṣàmúlò-ètò
LAD-400 3B	Àwọn ìtumọ̀ (450+ ede)	_Ìṣàmúlò-ètò	HuggingFace
_Ìṣàmúlò-ètò	Ìṣàmúlò-ètò àwòrán	BSD	GitHub
BRIA RMBG 2.0	Ìjádé àwọn ààyè-iṣẹ́	_Ìṣàmúlò-ètò	HuggingFace
Àwọn Àkọ́lé	Àwọn ààyè-iṣẹ́ àwọn àwòrán	_Ìṣàmúlò-ètò	GitHub
_Ṣẹ̀dà	Àwọn àwọn àwọ̀ àwòrán	MIT	GitHub
All-MiniLM-L6-v2	Àwọn ìṣàmúlò-ètò àkọlé	_Ìṣàmúlò-ètò	HuggingFace
Tésérákì	OCR	_Ìṣàmúlò-ètò	GitHub

Àtòjọ-ètò Àwọn Ààtò Ìṣàmúlò-ètò

Àwọn ìṣàfarawégbèyélú àwọn ìṣàmúlò-ètò àìdálẹ̀ tí a tí ṣé ìṣàmúlò-ètò àìdálẹ̀ nípa ìṣẹ̀dá ọ̀fẹ́ tí 15,000,000 tokè, tokè-ìdálẹ̀ tí a fi pamọ́ fun odun kan tí Pro, àti àwọn bọ́tìnì API nínú àwọn ìtàbọ̀ Pro (100,000 àwọn ìtàbọ̀ nínú oṣù kan). Ìṣàmúlò-ètò náà ń dá gbogbo àwọn àtòjọ-ẹ̀yàn tí a ǹró nínú àwọn àwòrán tí a ǹrọ́. Àwòrán tí a ǹró nínú àwọn àwòrán kò jẹ́ àwọn àwòrán: a lò tokè tí a tí rá.

Tí a bá fẹ́

Ó fi àwọn ìṣàmúlò-ètò pamọ́ (ògbèlù tàbí àwọn ìṣàmúlò-ètò ìṣàmúlò-ètò) àti àwọn ààyè-iṣẹ́ rẹ̀ nínú ìṣẹ̀dà àìfihàn àìfihàn OSI-ìdáràn
O tí a fi pamọ́ sípò, láti àwọn àgbèwọlé àti àwọn ìjádè nínú àwọn ọjọ́ 90 tókàn
Àwọn eniyan mìíràn lo o, ti a fi han nípa kan nínú: àwọn àwòrán 50 tí a fi pamọ́ sí GitHub, àwọn ìṣàmúlò-ètò 1,000 nínú oṣù kan, àti àwọn ìṣàmúlò-ètò tí a dájú
Àwọn àwọn ààyè-iṣẹ́ àwọn àwọn ààyè-iṣẹ́ Free.ai, àwọn àtòjọ-ẹ̀yàn àwọn àwọn àtòjọ-ẹ̀yàn àwọn

To apply, send the repository link and a link to the evidence of use (stars, download statistics or dependents) from the email address on your Free.ai account. Fikún láti inú àtòjọ-ẹ̀yàn

Wá Àwọn Àtòjọ-ẹ̀yàn Àwọn Ìṣàmúlò-ètò GPU

Àwọn Àtòjọ-Ìtàn

Yes. Every model we run on our GPU servers is open-source under permissive licenses -- Apache 2.0, MIT, or BSD. We deliberately exclude models with restrictive licenses like Meta's Llama license. You can inspect, use, and modify all models freely.

Meta's Llama license includes restrictions on commercial use for large companies and requires specific attribution. We only use models with truly permissive licenses (Apache 2.0, MIT, BSD) that allow unrestricted commercial and personal use by anyone.

Every model in our table links to its source on HuggingFace or GitHub. You can download the weights directly from these repositories and run them on your own hardware.

Qwen2.5-72B is our most capable chat model for complex reasoning and analysis. Qwen2.5-7B and Mistral-7B are faster options for everyday tasks. Phi-3 is excellent for efficient reasoning and math.

We use five text-to-speech models: Kokoro (Apache 2.0), Piper (MIT), MeloTTS (MIT), Chatterbox (MIT), and OuteTTS (Apache 2.0). Each has different strengths in voice quality, speed, and language support.

FLUX.1-schnell for fast generation (Apache 2.0), Stable Diffusion XL for high-quality images (OpenRAIL++), and Kandinsky 2.2 for artistic styles (Apache 2.0). For video, we use CogVideoX-2B, Wan 2.2 and HunyuanVideo.

If you have developed or know of an open-source model under a permissive license that you think we should host, contact us. We evaluate models based on quality, license compatibility, and user demand.

A free grant of 15,000,000 tokens plus API keys at the Pro request tier (100,000 requests per month) for maintainers of actively maintained open source projects with evidence of use. It covers the tools that run on our self-hosted models. Premium external models are not part of the grant and use purchased tokens. Apply with a link to your repository and to the evidence of use.

We evaluate every model before deploying it based on benchmark performance, real-world output quality, inference speed, and license compliance. Only models that meet our quality bar are added to the platform.

We use MadLAD-400 3B from Google, which supports 450+ languages under an Apache 2.0 license. It handles even low-resource languages that many commercial translation services do not support.

Real-ESRGAN (BSD) for image upscaling, BRIA RMBG 2.0 (Apache 2.0) for background removal, SAM (Apache 2.0) for image segmentation, and DeOldify (MIT) for photo colorization.

Kò: àwọn àwọn àwòrán inú inú bí GPT-5, Claude àti Gemini ṣé ní àwọn àwọn àwòrán inú inú, wọ́ inú àwọn

Free AI for Open Source

Àwọn ìṣàmúlò-ètò AI

Chat Àwọn ìṣàmúlò-ètò Àwọn

Àwọn ìṣàmúlò-ètò

Àwọn ìṣàmúlò-ètò àwòrán

Àwọn ìṣàmúlò-ètò Àkọ́kọ́

Àwọn ìṣàfarawé, àwọn ìṣàmúlò-ètò àti àwọn àwọn ìṣàmúlò-ètò mìíràn

Àtòjọ-ètò Àwọn Ààtò Ìṣàmúlò-ètò

Tí a bá fẹ́

Àwọn Àtòjọ-Ìtàn

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