GPU Hosting & AI Engineering Blog
Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Command R+ 104B Deployment
Cohere's flagship open-weights 104B RAG model needs serious hardware. Here is what it takes to host it on dedicated GPUs.
Latest Articles
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
Command R 35B Self-Hosted
Cohere's Command R is a 35B model tuned for RAG and tool use - self-hosting it gives you a capable…
CogVLM2 Self-Hosted Deployment
THUDM's CogVLM2 is a 19B-parameter vision-language model with strong visual grounding and OCR - a less-common but capable choice.
Codestral 22B Self-Hosted on a Dedicated GPU
Mistral's Codestral 22B is a dedicated coding model that beats many 30B+ generalists on programming tasks. Hosting it is straightforward.
Axolotl on a Dedicated GPU Server
Axolotl is the config-driven fine-tuning framework most production teams reach for. Here is how to set it up on a…
Ollama num_parallel and num_queue Tuning
Two Ollama environment variables control how many requests run in parallel versus queue. Defaults crash under moderate traffic.
Ollama Keep-Alive and Model Memory Tuning
Ollama unloads models from VRAM after idle. Adjust keep_alive to avoid cold-start latency or to share a GPU between models…
Nemotron 70B Self-Hosted
Nvidia's Nemotron 70B extends Llama 3.1 70B with RLHF and domain tuning. Hosting is similar to stock Llama 70B but…
Molmo 7B Self-Hosted Vision-Language Model
Allen AI's Molmo 7B is a compact, trained-from-scratch VLM with particularly strong pointing and counting capabilities.
Mixtral 8x22B on a Dedicated GPU
Mistral's Mixtral 8x22B is a 141B total / 39B active MoE that needs serious VRAM - but quantised it fits…
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