Almanac
← Events
4GitHub Trending (AI/LLM filtered)·27d ago

free-llm-api-resources: Curated List of Free LLM API Inference Endpoints

A GitHub repository maintained by cheahjs catalogues free LLM inference resources accessible via API, accumulating over 22,000 stars with 89 added today. The project serves as a community reference for developers seeking zero-cost access to hosted language model endpoints. High star count signals broad practitioner interest in inference cost reduction and accessible model APIs.

Related guides (2)

Related events (8)

3Github Trending·1mo ago·source ↗

vLLM: High-Throughput LLM Inference and Serving Engine Trending on GitHub

vLLM is an open-source Python library providing high-throughput and memory-efficient inference and serving for large language models. The project has accumulated over 80,500 GitHub stars with 98 new stars today, indicating continued strong community interest. It is a widely adopted inference backend in the AI/ML ecosystem, supporting PagedAttention and various optimization techniques for LLM deployment.

4Github Trending·10d ago·source ↗

LiteLLM AI gateway trending: 50K stars, unified interface for 100+ LLM APIs

LiteLLM is a Python SDK and proxy server providing a unified OpenAI-compatible interface to 100+ LLM APIs including Bedrock, Azure, OpenAI, VertexAI, Anthropic, and others. It includes cost tracking, guardrails, load balancing, and logging. The project is trending on GitHub with ~50K total stars and 141 new stars today, signaling continued strong adoption as an AI gateway layer.

4Hugging Face Blog·1mo ago·source ↗

Open-Source Text Generation & LLM Ecosystem at Hugging Face

Hugging Face published a blog post surveying the open-source LLM ecosystem as of mid-2023, covering text generation models, tooling, and deployment patterns available on the platform. The post highlights the breadth of open-weight models and associated infrastructure for inference and fine-tuning. It serves as a reference overview of the state of open-source LLMs at that point in time.

4Github Trending·24d ago·source ↗

Langfuse: Open Source LLM Engineering Platform Trending on GitHub

Langfuse is an open-source LLM engineering platform providing observability, metrics, evaluations, prompt management, and dataset tooling. It integrates with OpenTelemetry, LangChain, OpenAI SDK, and LiteLLM. The project has accumulated 28,075 GitHub stars with 89 new stars today, indicating sustained community traction. Backed by Y Combinator (W23), it represents a notable entry in the LLM ops/tooling ecosystem.

4Hugging Face Blog·1mo ago·source ↗

Deploy LLMs with Hugging Face Inference Endpoints

Hugging Face published a guide on deploying large language models using their Inference Endpoints service. The post covers how to set up scalable, production-ready LLM deployments with minimal infrastructure overhead. It targets developers looking to move from experimentation to hosted inference without managing raw compute.

4Github Trending·1mo ago·source ↗

awesome-llm-apps: 100+ Runnable AI Agent & RAG Application Examples

A curated GitHub repository collecting over 100 deployable AI agent and RAG (Retrieval-Augmented Generation) applications built with LLMs. The collection is designed for practical use — clone, customize, and ship. With 110,915 total stars and 202 added today, it reflects strong community interest in applied LLM tooling.

3Github Trending·8d ago·source ↗

mlx-lm: LLM inference library for Apple MLX framework trending on GitHub

mlx-lm is an open-source Python library for running LLMs using Apple's MLX framework, designed for Apple Silicon hardware. The repository has accumulated 5,817 stars with 43 new stars today, indicating steady community interest. It represents a key piece of the Apple-native ML inference ecosystem.

4Hugging Face Blog·1mo ago·source ↗

Bringing the Artificial Analysis LLM Performance Leaderboard to Hugging Face

Hugging Face is hosting the Artificial Analysis LLM Performance Leaderboard, which tracks inference performance metrics such as latency, throughput, and cost across multiple LLM providers. The leaderboard provides a standardized comparison of how different models perform in production deployment contexts rather than purely capability benchmarks. This collaboration brings infrastructure and deployment performance data into the Hugging Face ecosystem.