Together GPU Clusters auto repair detects GPU, host and fabric faults, picks the lightest fix, and lets you decide per fault ...

MiniMax M3.1 Flash is a 428B parameter (23B active) native multimodal MoE model for coding, agentic workflows, computer use, and security research, with text, image, and video input and 1M context.

Introducing Together Link: Run open models inside the harness you already use → ...

Build with Muse Spark Open. See the license and usage policy. Muse Spark Open is the coding-optimized open weights model from Meta, trained specifically for agentic coding workflows: higher ...

NVIDIA Nemotron 3.5 Super VL is an open-weight multimodal model designed for visual reasoning and long-running AI agents. It combines text, image, document, and video understanding with agentic ...

40+ Models Chosen for Production...40+ Models Chosen for Production...40+ Models Chosen for Production... We are introducing Together Post-Training, a new service for building custom models on our ...

Updated DeepSeek V4.1 Flash release: a 552B multimodal MoE activating 8B-16B per token, with 1M context, faster task completion, and shorter outputs than the original V4.1 Flash.

Beam is Reflection's first open model: a Mixture-of-Experts, decoder-only transformer with roughly 501B total parameters and 23B active per token, built for the two workloads that lead frontier ...

Muse Spark Open, the coding-optimized open weights model from Meta, trained for agentic workflows with reliable tool calling, deep codebase understanding, multimodal perception, and a 1M-token context ...

Fine-tuning an LLM means continuing to train a pretrained model on a smaller, task-specific dataset so its weights shift toward the behavior you want: a format, a style, a task skill. Prompting steers ...

RAG vs. fine-tuning is a choice between two ways of adapting an LLM to your application. Retrieval-augmented generation (RAG) retrieves relevant external documents at query time and puts them in the ...