Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
Benchmark data for CodeLlama 34B inference speed across GPUs with INT4 and INT8 quantisation results and cost analysis for dedicated GPU hosting.
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
Benchmark results for Mixtral 8x7B MoE inference speed across GPUs with quantisation data and cost-efficiency analysis for dedicated GPU hosting.
Benchmark results for DeepSeek R1 Distill inference speed across six GPUs, comparing FP16, INT8, and INT4 quantisation with cost-per-token analysis.
Benchmark data for Google Gemma 2 27B inference speed across GPUs with quantisation comparisons and cost-per-token analysis for UK dedicated…
Yes, the RTX 5090 can run Mixtral 8x7B in INT4 quantisation with 32GB VRAM. Here are the VRAM requirements, performance…
Yes, the RTX 5080 runs Flux.1 Schnell in FP8 and Dev in NF4 with strong performance. Here are the VRAM…
The RTX 3050 cannot run DeepSeek R1 or V3 at usable quality due to its 6GB VRAM. Here is what…
Yes, the RTX 5080 can run Whisper and a 7B LLM simultaneously with 16GB VRAM. Here is how to allocate…
Yes, the RTX 5080 runs SDXL at full quality with fast generation times. Here are the VRAM numbers, benchmarks, and…
Yes, the RTX 5080 runs Mistral 7B in full FP16 precision with room to spare. Here are the benchmarks and…
Find exactly what you need — from GPU benchmarks to deployment tutorials.
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