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.
RTX 5060 Ti 16GB for Llama 3 70B INT4 – Does It Fit?
Can you squeeze Llama 3 70B onto a single 16GB Blackwell card? Aggressive quantisation and CPU offload get you there but production isn't realistic.
RTX 5060 Ti 16GB for Llama 3 8B
Llama 3 8B is the most-hosted model in 2026. Full deployment guide on Blackwell 16GB - VRAM fit, vLLM config,…
RTX 5060 Ti 16GB for Mistral 7B
Mistral 7B on Blackwell 16GB - VRAM fit, deployment config, throughput across precisions, and concurrency targets for production.
RTX 5060 Ti 16GB for Mistral Nemo 12B
Mistral Nemo 12B + 128k context on Blackwell 16GB. KV cache math, context budget tradeoffs, and multi-user tuning for long-document…
RTX 5060 Ti 16GB for Mistral Small 3
Mistral Small 3 at 24B pushes the 16GB boundary. Detailed fit analysis, AWQ deployment config, and whether it's viable for…
RTX 5060 Ti 16GB for Phi-3-medium
Phi-3-medium (14B) at AWQ runs comfortably on Blackwell 16GB - a capable Microsoft reasoning model at mid-tier.
RTX 5060 Ti 16GB for Phi-3-mini
Phi-3-mini delivers extreme concurrency on Blackwell 16GB - ideal for high-QPS classification, lightweight chat, and routing layers.
RTX 5060 Ti 16GB for Qwen 2.5 14B
Qwen 2.5 14B at AWQ on Blackwell 16GB - the sweet spot for stronger reasoning than 7B while staying single-card…
RTX 5060 Ti 16GB for Qwen 2.5 7B
Qwen 2.5 7B on Blackwell 16GB - bilingual English/Chinese production LLM with comfortable concurrency and 32k context.
RTX 5060 Ti 16GB for Qwen Coder 7B
Qwen Coder 7B on Blackwell 16GB - self-hosted IDE autocomplete and code chat with fill-in-middle support.
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Deploy YOLO, PaddleOCR, Stable Diffusion, and other vision models on GPU-accelerated servers.
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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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