How many GPUs are needed to train 7B / 13B / 70B models?

Q: How many GPUs are needed to train 7B / 13B / 70B models?

Estimate VRAM needs backward: Full-parameter fine-tuning (bf16) requires roughly ‘parameter count × 16–20 GB’—e.g., 7B ≈ 120–160 GB (minimum 2×A100 80GB), 13B ≈ 240–300 GB (4×A100 80GB), 70B ≈ 1.1 TB+ (16×H100-class cluster). Quantized inference needs only ‘parameter count × 0.5–1 GB’—e.g., 7B fits on one 24GB card, 70B fits on one H200 141GB or 2×A100 80GB. Calculate VRAM first—renting extra GPUs wastes money.

Last updated: 2026-11-12 15:45 · Always refer to the platform’s official order page · Free API: rentgpu.link/api/prices

Straight answer: Back-calculate from VRAM: Full-parameter fine-tuning (bf16) requires roughly “parameter count × 16–20 GB”: 7B ≈ 120–160 GB (minimum 2×A100 80GB), 13B ≈ 240–300 GB (4×A100 80GB), 70B ≈ 1.1 TB+ (16×H100-level cluster). Quantized inference needs only “parameter count × 0.5–1 GB”: 7B fits on one 24GB GPU; 70B fits on one H200 141GB or two A100 80GB GPUs. Calculate VRAM needs first—renting extra GPUs burns money needlessly.

GPU model	Hourly rate per GPU	Reference Combinations
RTX 4090	¥1.15/hour	1 GPU for approx. ¥1/hour
RTX 4090	¥1.15/hour	2 GPUs for approx. ¥2/hour
A100 80GB	¥5.47/hour	1 GPU for approx. ¥5/hour
A100 80GB	¥5.47/hour	2 GPUs for approx. ¥11/hour
H100 80GB	¥8.28/hour	1 GPU for approx. ¥8/hour
H200 141GB	¥16.49/hour	1 GPU for approx. ¥16/hour

Why the factor is 16–20×

Full-parameter training requires simultaneous residency of weights (2 bytes/parameter) + gradients (2) + optimizer states (8–12, Adam-family) + activations and buffers—totaling ~16–20 bytes/parameter. QLoRA quantizes the base model to 4-bit and trains only a small adapter set, reducing memory footprint to under 1 byte/parameter—hence why “a student can fine-tune a 7B model on a single RTX 4090”.

Methodology

Above figures reflect community-consensus order-of-magnitude estimates; actual VRAM usage varies significantly depending on framework, sequence length, and parallelization strategy — benchmarking is strongly recommended. Prices are live public quotes scraped by this site every 45 minutes.

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How many GPUs are needed to train 7B / 13B / 70B models?

Why the factor is 16–20×

Methodology

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