How to Manage Funding Your Runpod Account
This guide breaks down everything you need to know about billing on Runpod, how credits are applied, what gets charged, and how to set up automatic or.
RunPod7 min read
Runpod
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Runpod RoundUp 2: 32k Token Context LLMs, StabilityAI
This week's Runpod RoundUp covers major releases including Llama-2 with 32k context support, SDXL 1.0's public release, and StabilityAI's new Stable.
RunPod3 min readHow to Cut LLM Inference Latency and Cost
Learn how to reduce LLM inference costs and latency using quantization, vLLM, SGLang, and speculative decoding without upgrading your hardware.
RunPod13 min readRunpod Sponsors CivitAI’s Project Odyssey 2024
Runpod is proud to support Project Odyssey, CivitAI’s groundbreaking open-source AI film competition. Learn how we’re powering creators around the world.
RunPod4 min readGPU Cloud vs On-Prem Clusters: A Cost Breakdown
We crunched the numbers: deploying 4x A100s on Runpod's GPU cloud can save over $124,000 versus an on-prem cluster across 3 years. Learn why cloud beats.
RunPod8 min readHow to Achieve True SSH in Runpod
This tutorial guides users through setting up a true SSH daemon on Runpod, enabling functionalities like SCP and IDE connections. It covers selecting a.
RunPod4 min readMochi 1: New State of the Art in Open-Source Text-to-Video
Mochi 1 pushes the boundaries of open-source video generation. Learn what makes it special, what’s new in v1, and how to deploy it on Runpod.
RunPod5 min readRunpod Roundup 5: Vision, Code LLMs, and Bias Detection
his week's roundup covers Alibaba's vision-language model Qwen-VL, Meta's new code-focused LLM Code Llama, and FACET, a benchmark for detecting bias in.
RunPod3 min readHybridize Images With Image Mixer Before Running Through img2img
Image Mixer lets you blend multiple source images into a hybrid input for img2img in Stable Diffusion. This guide walks through setup, usage, and how to.
RunPod4 min readRAG vs. Fine-Tuning: Which Strategy is Best for Customizing LLMs?
RAG and fine-tuning are two powerful strategies for adapting large language models (LLMs) to domain-specific tasks. This post compares their use cases.
RunPod9 min readSupercharge Your LLMs with SGLang: Boost Performance and Customization
Discover how to boost your LLM inference performance and customize responses using SGLang, an innovative framework for structured LLM workflows.
RunPod8 min readQuantization Methods Compared: Speed vs. Accuracy in Model Deployment
Explore the trade-offs between post-training, quantization-aware training, mixed precision, and dynamic quantization. Learn how each method impacts model.
RunPod8 min readRAG vs. Fine-Tuning: Which Is Best for Your LLM?
Retrieval-Augmented Generation (RAG) and fine-tuning are powerful ways to adapt large language models. Learn the key differences, trade-offs, and when to.
RunPod9 min readPartnering with Defined AI to Bridge the Data Wealth Gap
Runpod and Defined.ai launch a pilot program to provide startups with access to high-quality training data and compute, enabling sector-specific.
RunPod4 min readStreamline GPU Cloud Management with Runpod’s New REST API
Runpod’s new REST API lets you manage GPU workloads programmatically, launch, scale, and monitor pods without ever touching the dashboard.
RunPod4 min readGlobal Volumes are now in beta for Serverless endpoints
Attach a Global Volume to a Runpod Serverless endpoint and your workers start in any data center with your GPU types. Store model weights once, read anywhere.
RunPod5 min readIntroduction to vLLM and PagedAttention
Learn how vLLM achieves higher throughput than Hugging Face Transformers by using PagedAttention to eliminate memory waste, boost inference.
RunPod12 min readAvoid Errors by Selecting the Proper Resources for Your Pod
Common errors when spinning up pods often stem from insufficient container space or RAM/VRAM. This post explains how to identify and fix both issues by.
RunPod5 min read
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