GPU Hosting & AI Engineering Blog
Benchmarks, GPU comparisons, deployment guides, and cost analysis — everything you need to run AI on dedicated GPU servers.
LLaMA 3 8B on RTX 3050: Performance Benchmark & Cost, Category: Benchmarks, Slug: llama-3-8b-on-rtx-3050-benchmark, Excerpt: LLaMA 3 8B benchmarked on RTX 3050: 8 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
LLaMA 3 8B benchmarked on RTX 3050: 8 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment configuration.
Latest Articles
Fresh benchmarks, comparisons, and deployment guides from the GigaGPU team.
DeepSeek 7B on RTX 4060: Performance Benchmark & Cost, Category: Benchmarks, Slug: deepseek-7b-on-rtx-4060-benchmark, Excerpt: DeepSeek 7B benchmarked on RTX 4060: 22.0 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
DeepSeek 7B benchmarked on RTX 4060: 22.0 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment…
DeepSeek 7B on RTX 3050: Performance Benchmark & Cost, Category: Benchmarks, Slug: deepseek-7b-on-rtx-3050-benchmark, Excerpt: DeepSeek 7B benchmarked on RTX 3050: 10.0 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
DeepSeek 7B benchmarked on RTX 3050: 10.0 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment…
LLaMA 3 8B on RTX 5090: Performance Benchmark & Cost, Category: Benchmarks, Slug: llama-3-8b-on-rtx-5090-benchmark, Excerpt: LLaMA 3 8B benchmarked on RTX 5090: 100 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
LLaMA 3 8B benchmarked on RTX 5090: 100 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration.
LLaMA 3 8B on RTX 5080: Performance Benchmark & Cost, Category: Benchmarks, Slug: llama-3-8b-on-rtx-5080-benchmark, Excerpt: LLaMA 3 8B benchmarked on RTX 5080: 82 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
LLaMA 3 8B benchmarked on RTX 5080: 82 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration.
Mistral 7B on RTX 3050: Performance Benchmark & Cost, Category: Benchmarks, Slug: mistral-7b-on-rtx-3050-benchmark, Excerpt: Mistral 7B benchmarked on RTX 3050: 10.0 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
Mistral 7B benchmarked on RTX 3050: 10.0 tok/s at 4-bit GGUF Q4_K_M, VRAM usage, cost per 1M tokens, and deployment…
DeepSeek 7B on RTX 5090: Performance Benchmark & Cost, Category: Benchmarks, Slug: deepseek-7b-on-rtx-5090-benchmark, Excerpt: DeepSeek 7B benchmarked on RTX 5090: 95.0 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
DeepSeek 7B benchmarked on RTX 5090: 95.0 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration.
DeepSeek 7B on RTX 5080: Performance Benchmark & Cost, Category: Benchmarks, Slug: deepseek-7b-on-rtx-5080-benchmark, Excerpt: DeepSeek 7B benchmarked on RTX 5080: 68.0 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
DeepSeek 7B benchmarked on RTX 5080: 68.0 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration.
DeepSeek 7B on RTX 3090: Performance Benchmark & Cost, Category: Benchmarks, Slug: deepseek-7b-on-rtx-3090-benchmark, Excerpt: DeepSeek 7B benchmarked on RTX 3090: 44.0 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
DeepSeek 7B benchmarked on RTX 3090: 44.0 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration.
DeepSeek 7B on RTX 4060 Ti: Performance Benchmark & Cost, Category: Benchmarks, Slug: deepseek-7b-on-rtx-4060-ti-benchmark, Excerpt: DeepSeek 7B benchmarked on RTX 4060 Ti: 32.0 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration., Internal links: 9 –>
DeepSeek 7B benchmarked on RTX 4060 Ti: 32.0 tok/s at FP16, VRAM usage, cost per 1M tokens, and deployment configuration.
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