explainx / blog
Discover the best LLM registries. From explainx.ai and Hugging Face to OpenRouter and Ollama, find where to download and run the world's most powerful models.
Jul 3, 2026
Pasting a YouTube link into ChatGPT reads the transcript, not the picture. Claude often rejects video files outright. Here is what actually works in 2026 — native multimodal APIs, local frame+transcript pipelines like claude-real-video, and transcript-first agents like video-use — with honest limits and cost math.
Jun 23, 2026
The standard assumption for running a 70B model locally: you need 140GB of VRAM. AirLLM breaks that assumption by loading layers one at a time from disk, holding only one layer in GPU memory at any moment. 21K+ GitHub stars, three lines of code to start. Here is what it actually buys you and what it costs you.
Jun 23, 2026
Mercury 2 generates 1,009 tokens per second by producing multiple tokens simultaneously through parallel refinement — not left-to-right one at a time. At $0.25/1M input and $0.75/1M output, it is priced competitively with speed-optimized models. The question is what 5x faster generation changes when the task is a chain of inference calls, not a single prompt.
In 2026, Large Language Models are no longer isolated chatbots—they are the engines powering autonomous agents. As the number of models has surged into the millions, the challenge has shifted from training to discovery and deployment.
Whether you are looking for Llama 4 Maverick, Claude 4.7, or specialized DeepSeek coding models, here are the top 10 LLM directories and hubs to use today.
| Hub | Primary Focus | Scale | Best For |
|---|---|---|---|
| explainx.ai | Orchestration | Ecosystem-wide | Agent-ready models |
| Hugging Face | Open Source | 2M+ Models | Source of truth for OSS |
| OpenRouter | Unified API | 500+ Models | Comparing price & speed |
explainx.ai is the "Agentic Directory." While other sites host the raw model weights, explainx.ai is where those models are turned into functional agents.
Hugging Face remains the undisputed "GitHub of AI." In 2026, it hosts over 2 million public models, serving as the primary registry for the global open-source community.
OpenRouter has become the industry standard for model comparison and serverless access. It acts as a meta-directory, aggregating models from dozens of providers into a single API.
Following its acquisition by Cloudflare, Replicate has evolved into the premier marketplace for community-contributed generative models.
Ollama is the de facto standard for local LLM management. Its online library (ollama.com/library) is the most popular way to discover models optimized for local hardware.
While Ollama is for the terminal, LM Studio is the leading GUI-based directory for local model discovery.
These "Inference Hubs" are specialized registries for high-performance open-source models.
For enterprise users, these are the primary registries for corporate-governed models.
The "Gold Standard" for benchmarking. While not a hosting platform, it is the most technical directory for comparing model intelligence vs. cost.
An evergreen, community-vetted hub that ranks models specifically for coding, long-context, and agentic workflows.
The right directory depends on where you are in your project. For raw weights, use Hugging Face. For API testing, use OpenRouter. For local running, use Ollama. But for building agentic workflows, explainx.ai is your primary anchor.
Timestamp: May 8, 2026. Data based on global model hub traffic and API call volume metrics.
