# llama
6 tools tagged
Showing 6 of 6 tools
Cerebras
Wafer-scale inference at thousands of tokens per second
Cerebras Inference serves open-weight LLMs like Llama, Qwen, and GPT-OSS on wafer-scale CS-3 chips through an OpenAI-compatible API, benchmarking between 1,800 and 2,600 output tokens per second on Llama 3.1 8B and several hundred on 70B models. A free tier offers one million tokens per day with no credit card, while paid pay-per-token pricing starts at $0.04 per million tokens for the smaller Llama models.
AWS Bedrock
Managed foundation models on AWS
Fully managed AWS service providing enterprise access to 100+ foundation models from Anthropic, Meta, Mistral, Cohere, and Amazon's Nova family through a single API. Bedrock includes AgentCore for agent runtime, Knowledge Bases for RAG, Guardrails blocking 88% of harmful content, plus Model Distillation, Prompt Caching, and Intelligent Prompt Routing for cost optimization.
Fireworks AI
Production-grade inference with serverless and on-demand GPUs
High-performance inference platform serving open-source and custom AI models at global scale, processing 13+ trillion tokens daily at ~180K requests per second. Fireworks AI delivers 1,000+ tokens per second on large models through quantization-aware tuning and adaptive speculation, with serverless, fine-tuning, and dedicated GPU options across text, image, and audio modalities.
Groq
Ultra-fast LPU inference for open-weight models
Groq is an AI inference provider built around custom Language Processing Unit (LPU) hardware for low-latency open-weight model serving. GroqCloud exposes an OpenAI-compatible API for Llama, GPT-OSS, Qwen, Kimi, DeepSeek, Gemma, Whisper, and related models, with high token-throughput positioning, model-specific rate limits, and usage-based pricing.
Together AI
Open-weight inference, fine-tuning, and GPU-cloud platform
Together AI is a cloud platform for running, fine-tuning, batching, and training open-weight AI models. It supports serverless inference, dedicated endpoints, LoRA and full fine-tuning, GPU clusters, code-execution sandboxes, and async batch jobs up to 30B tokens per model. Current docs list fast-moving families such as Qwen, Kimi, GLM, GPT-OSS, DeepSeek, Llama, MiniMax, and Mistral.
Ollama
Run LLMs locally with one command
Tool for running large language models locally on your machine with a simple CLI interface. Download and run Llama 3, Mistral, Gemma, Phi, Code Llama, and dozens of other open-source models with a single command. Features model management, GPU acceleration (NVIDIA/AMD/Apple Silicon), OpenAI-compatible API server, Modelfile for customization, and multi-model switching. Ideal for offline AI development, privacy-sensitive use cases, and local testing. 120K+ GitHub stars.