Deploy larger language models on existing hardware with advanced GPU memory optimization on Runpod—use gradient checkpointing, model sharding, and quantization to reduce memory by up to 80% while maintaining performance at scale.

Optimize AI models for production with quantization on Runpod—reduce memory usage by up to 80% and boost inference speed using 8-bit or 4-bit precision on A100/H100 GPUs, with Dockerized workflows and serverless deployment at scale.

Deploy low-latency, privacy-first AI models at the edge using Runpod—prototype and optimize GPU-accelerated inference on RTX and Jetson-class hardware, then scale with Dockerized workflows, secure containers, and serverless endpoints.

Train trillion-scale models efficiently with multi-GPU infrastructure on Runpod—use A100/H100 clusters, advanced parallelism strategies (data, model, pipeline), and pay-per-second pricing to accelerate training from months to days.

Generate high-quality 10-second AI videos with CogVideoX on Runpod—leverage L40S GPUs, Dockerized PyTorch workflows, and scalable serverless infrastructure to produce compelling motion-accurate content for marketing, animation, and prototyping.

Create lifelike speech with Parler-TTS on Runpod—generate expressive, multi-speaker audio using RTX 4090 GPUs, Dockerized TTS environments, and real-time API endpoints for accessibility, education, and virtual assistants.

Fine-tune DeepSeek-Coder V2 on Runpod’s A100 GPUs to accelerate code generation and debugging—customize multilingual coding models using Dockerized environments, scalable training, and secure serverless deployment.

Deploy 01.AI’s Yi-1.5 on Runpod to power vision-language AI—run image-text fusion tasks like captioning and VQA using A100 GPUs, Dockerized PyTorch environments, and scalable serverless endpoints with per-second billing.

Generate high-fidelity 3D models in seconds with TripoSR on Runpod—leverage L40S GPUs, Dockerized PyTorch workflows, and scalable infrastructure for fast, texture-accurate mesh creation in design, AR, and gaming pipelines.