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Run and consume LLMs in the cloud - pick a tier, provision, deploy, connect to one gateway endpoint, secure, set budgets, benchmark, scale, update and tear down. Covers frontier APIs (OpenAI, Anthropic Claude, Google Gemini), managed open-model APIs (Together…
Fine-tune open-weight LLMs locally (NVIDIA DGX Spark unified memory, consumer RTX GPUs) or on rented cloud GPUs. Covers deciding whether to fine-tune vs prompting or RAG, dataset prep (chat templates, messages JSONL, ShareGPT/Alpaca, preference pairs, dedup,…
Connect coding agents, IDE extensions, chat UIs and SDK apps to any OpenAI- or Anthropic-compatible LLM endpoint (local engine, self-hosted server, gateway such as LiteLLM, or cloud API). Use when configuring Claude Code (ANTHROPIC_BASE_URL,…
Evaluate LLMs on your own tasks against any OpenAI-compatible endpoint (local llama.cpp/Ollama, self-hosted vLLM/SGLang behind LiteLLM or llama-swap, or a cloud API). Use when choosing between models or endpoints, building a golden set from real prompts, A/B…
Put one OpenAI- and Anthropic-compatible endpoint in front of many local and cloud LLM providers. Use when choosing an LLM gateway (LiteLLM proxy, OpenRouter, Portkey, Envoy AI Gateway / Agent Router, Kong AI Gateway, Cloudflare AI Gateway), installing the…
Metrics, tracing, logging, cost tracking and alerting for LLM serving and LLM apps. Use when instrumenting or debugging vLLM, SGLang, llama.cpp server, TGI or llama-swap /metrics endpoints; scraping them with Prometheus and building Grafana dashboards (TTFT,…
Run LLMs locally on a laptop or desktop (macOS, Windows, Linux) with Ollama, LM Studio, llama.cpp (llama-server) or MLX (mlx-lm). Use when the user wants to install a local runtime, pick and size a model or GGUF/MLX quant for their RAM or VRAM (weights + KV…
Produce quantized LLM checkpoints and publish them. Covers GGUF (llama.cpp convert_hf_to_gguf.py, llama-quantize, llama-imatrix; Q4_K_M, Q8_0, IQ4_XS), EXL3 (ExLlamaV3 convert.py, TabbyAPI), AWQ / GPTQ / FP8 / NVFP4 with LLM Compressor (oneshot,…
Self-host generative media servers (image, video, speech-to-text, text-to-speech) in the same stack as your LLMs, behind a LiteLLM gateway and llama-swap. Covers stable-diffusion.cpp sd-server and ComfyUI for images; ComfyUI workflows for open video models…
Plan, set up, operate, update, benchmark, optimize and clean up a self-hosted LLM and generative-AI serving stack on your own Linux servers with NVIDIA GPUs, with NVIDIA DGX Spark (GB10, single or dual node over ConnectX-7) as the first-class profile. Builds…
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