Free AI Hosting
Host AI models for free. GPU access, API hosting, and cloud deployment.
ಮೇಘದ ಮೇಲೆ హోರ್ಬಾಶೆಯಾಗಿತ್ತು
Free.ai ಅನ್ವೇಷಕಗಳನ್ನು ಬಳಸು. zio setup, ಶೂನ್ಯವಾದ ಸುರಕ್ಷತಾ ವ್ಯವಸ್ಥೆ. ಎಲ್ಲಾ ಮಾದರಿಗಳು API ಅಥವ ಜಾಲ UI ಅನ್ನು ಬಳಸಿಕೊಂಡು ಪೂರ್ವ ಲೋಡ್ ಮಾಡಲ್ಪಡುತ್ತವೆ.
ಈಗ ಲಭ್ಯವಿರುವಸ್ವಯಂ-ವಿವಾಹಿತವನ್ನು ಚಲಾಯಿಸಿ
ನಿಮ್ಮ ಸ್ವಂತ ಯಂತ್ರಾಂಶಕ್ಕೆ ನಮ್ಮ ತೆರೆದ ತಾಣ AI മോഡರ್ಗಳನ್ನು ಚಲಾಯಿಸಿ. GPU ಬೆಂಬಲದೊಂದಿಗೆ ಚಿತ್ರಗಳನ್ನು, ಆಕರ್ಷಕವಾಗಿ ಸಂರಚಿಸಲಾಗಿದೆ.
ಸ್ವ- ಸಾರ್ಜಿತನೋಡಿಕೊಳ್ಳಲಾದ ಖಾಸಗಿ
GPU ಪರಿಚಾರಕಗಳು ನಮ್ಮನ್ನು ನೋಡಿಕೊಳ್ಳುತ್ತಿದ್ದು, ನಿಮ್ಮ ಇಷ್ಟವಾದ ಮೋಡ ಪ್ರದೇಶದಲ್ಲಿ ಆವಶ್ಯಪಡಿಸಿದವು. ಪೂರ್ಣ ದತ್ತಾಂಶವನ್ನು ಪ್ರತ್ಯೇಕಗೊಳಿಸಲಾಗಿದೆ ಮತ್ತು ಗ್ರಾಹಕೀಯ SLA.
ಮಧ್ಯಮಸ್ವಪ್ರೇಮಿಕ ಏಕಪಣೀಯ
ನಮ್ಮ ಎಲ್ಲಾ ಮಾದರಿಗಳು ತೆರೆದಿರುವ (ಸಾಕೆಟ್) Apache 2.0 / MIT ನಿಮ್ಮ ಸ್ವಂತ GPUT ಅನ್ನು ಚಲಾಯಿಸಬಹುದು:
# Pull and run a model with Docker
docker pull ghcr.io/free-ai/inference:latest
docker run --gpus all -p 8000:8000 ghcr.io/free-ai/inference:latest \
--model qwen2.5-72b --quantization awqಕನಿಷ್ಟ ಆವಶ್ಯಕತೆಗಳು
- NVIIDಯ 24 GB+ ವ್ಯಾರುಮಾಂಸ (RTX 4090, A5000, A100)
- CUDIA 12.0+ ಮತ್ತು NVITEA ಆರ್ಟಲ್ಗೆ ಸೇರಿದ ಡಾಕರ್
- ೧೬GB+ ವ್ಯವಸ್ಥೆ RAM, ಪ್ರತಿಮಾಪನದಲ್ಲಿ ೧೦ GB+ ಶೇಖರಣೆ
- 72B ಅಕ್ಷಾಂಶಗಳ ಮಾದರಿಗಳು: 80GB VRAM (A100) ಅಥವಾ ಬಹು- GPU ಸಿದ್ಧತೆ
ಏಕೆ ಸ್ವ - ಪ್ರೇಕ್ಷಣೀಯ?
- ದತ್ತಾಂಶದ ಸುರಕ್ಷತೆ — Your data never leaves your servers
- ಅನುಪಾತಗಳಿಲ್ಲ — Unlimited inference on your hardware
- ಹೊರವಿನ್ಯಾಸ — Meet data residency requirements
- ಗ್ರಾಹಕೀಯಗೊಳಿಸುವಿಕೆ — Fine-tune models on your data
- ವೆಚ್ಚ ನಿಯಂತ್ರಣ — Fixed hardware costs, no per-token fees
- ಎയര്- ಗಡಿಗೆComment — Runs fully offline
FAQ
Three options: Cloud Hosted (use our infrastructure, zero setup), Docker Self-Hosted (run models on your own GPU hardware), and Managed Private (dedicated GPU servers managed by us in your preferred region).
You need an NVIDIA GPU with 24GB+ VRAM (RTX 4090, A5000, A100), CUDA 12.0+, Docker with NVIDIA Container Toolkit, 16GB+ system RAM, and 100GB+ storage per model. For 72B parameter models, you need 80GB VRAM or a multi-GPU setup.
Yes. Self-hosted deployments run fully offline once the Docker images and model weights are downloaded. This is ideal for air-gapped environments and sensitive data processing.
Pull our Docker image and run it with GPU support. The command is: docker run --gpus all -p 8000:8000 ghcr.io/free-ai/inference:latest --model qwen2.5-72b --quantization awq. The container handles model loading and serves an API endpoint.
All self-hosted models use permissive open-source licenses -- Apache 2.0, MIT, or BSD. You can use them commercially without restrictions. We deliberately exclude models with restrictive licenses like Meta's Llama license.
Managed private hosting gives you dedicated GPU servers in your preferred cloud region, fully managed by our team. We handle setup, patching, model updates, and monitoring. You get full data isolation with an enterprise SLA.
Yes. Since all models are open-source, you can fine-tune them on your own data using standard training frameworks like Hugging Face Transformers. Our Docker images are compatible with popular fine-tuning tools.
Contact our sales team to discuss a trial period. We typically offer a short evaluation period for enterprise prospects to test managed private hosting before committing to a long-term plan.
Cloud hosting uses the standard token-based pricing. Self-hosted is free -- you only pay for your own hardware and electricity. Managed private hosting is priced based on GPU allocation, region, and SLA level.
Yes. You can self-host specific models for high-volume or sensitive workloads while using the Free.ai cloud for everything else. The API format is identical, making it easy to route requests between your infrastructure and ours.
We provide documentation, Docker images, and community support for self-hosted deployments. Managed private hosting includes full technical support, monitoring, and a dedicated account manager.
Cloud hosted is best for teams that want zero maintenance. Self-hosted is ideal for data privacy, compliance, or unlimited usage on your own hardware. Managed private is the best of both worlds -- full data isolation with no operational burden.