Model Guides
Step-by-step setup guides for specific AI models on dedicated GPU servers. From LLM deployment to vision model hosting and speech model hosting, each guide includes configuration, optimisation tips, and GPU recommendations.
8B LLM VRAM Requirements: Llama 3, Qwen, Phi-3 and the Rest
Exactly how much VRAM 8B-class language models need at FP16, FP8, and AWQ-INT4 — plus KV cache for long-context deployments.
Context Budget on the RTX 5060 Ti 16 GB: How Much Context Can You Afford?
Context length costs VRAM. On a 16 GB card, the trade-off between long context, model size, and concurrent users is…
FP8 Llama 3 Deployment on the RTX 5060 Ti 16 GB
Llama 3.1 8B at FP8 is the most cost-effective LLM deployment we benchmark. Here is the recipe on a 16…
FLUX.1 vs Stable Diffusion 3.5: Which Open Image Model in 2026?
FLUX.1 dev and Stable Diffusion 3.5 Large are the two strongest open image models in 2026. Quality, speed, hardware, and…
Multimodal LLM Deployment Guide: Vision-Language Models on Self-Hosted GPUs
Llama 3.2 Vision, Qwen 2.5 VL, MiniCPM-V — the strongest open-weight vision-language models in 2026 and how to deploy them.
Self-Hosted Mistral Small 22B Deployment Guide
Mistral Small 22B is the right model when 7B is not enough but 70B is overkill. Here is the deployment…
Self-Hosted Stable Diffusion 3.5 Large Deployment Guide
SD 3.5 Large is Stability AI's strongest open image model. Here is the ComfyUI deployment recipe on dedicated GPU hardware,…
Qwen 2.5 14B Self-Hosted Deployment on Dedicated GPU
Qwen 2.5 14B is the production sweet spot of the Qwen family. Here is the deployment runbook for hosting it…
Llama 3.1 70B vs Llama 3.3 70B: Worth the Upgrade?
Meta's Llama 3.3 70B is a text-only refresh of 3.1. Same hardware profile, better reasoning. Here is whether it is…
Self-Hosted Wan 2.1 Video Generation Deployment Guide
Wan 2.1 (Alibaba) is the strongest open-weight video generation model in 2026. Here is the deployment recipe on dedicated GPU…
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Deploy Whisper, Coqui, Bark, and other speech models with low-latency inference.
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Vision-language models, audio-language models — deploy multimodal AI on dedicated GPUs.
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Real-world tokens per second data across every GPU we offer, tested on popular LLMs.
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