FINE-TUNING IN 2026
Fine-tuning accounts for 35-45% of GPU rental demand from mid-stage AI companies in 2026. Llama 4 spans from 8B to 405B parameters with Scout (17B MoE) and Maverick (72B MoE) variants. Each model size and fine-tuning technique has distinct GPU requirements, determining whether a team rents 1 GPU for 3 hours or 64 GPUs for 2 weeks. The economic range spans $15 to $150,000 per fine-tuning run.
LORA COST BREAKDOWN
LoRA on Llama 4 Scout (17B MoE) requires 40 GB VRAM at FP8, fitting on single H100. A 3-hour run costs $7.50-10.50 on spot H100. Llama 4 Maverick (72B MoE) needs 96 GB VRAM, requiring H200 or 2x H100 at $8.00-12.00/hr for 6-8 hours totaling $48-96 per run. Llama 4 405B LoRA needs 320 GB via 4x H100 NVLink at $10.00-14.00/hr for 12-24 hours totaling $120-336.
| Model | Technique | GPUs | Hours | Total Cost |
|---|---|---|---|---|
| Scout 17B | LoRA | 1x H100 | 3 | $7.50-10.50 |
| Maverick 72B | LoRA | 1x H200 | 8 | $48-96 |
| Llama 4 405B | LoRA | 4x H100 | 24 | $120-336 |
| Scout 17B | QLoRA | 1x L40S | 4 | $5.60-8.00 |
| Maverick 72B | QLoRA | 1x H100 | 12 | $30-42 |
| Llama 4 405B | Full SFT | 64x H100 | 336 | $67,200-100,800 |
QLORA COSTS
QLoRA reduces memory 2-4x through INT4 normalization. Scout 17B fits on single L40S at $1.40/hr for 4 hours at $5.60-8.00 total. Maverick 72B QLoRA on H100 uses 48 GB VRAM for 12 hours at $30-42 total. Quality degradation versus full LoRA is 1-3% on downstream tasks. QLoRA is the most cost-effective option for teams validating fine-tuning approaches before committing to full runs.
FULL SFT COSTS
Full supervised fine-tuning of Llama 4 405B requires 64 H100s for 2 weeks at $10-14/hr per GPU: total $67,200-100,800. Maverick 72B full SFT needs 8 H100s for 5 days at $4,800-7,200 total. Scout 17B full SFT needs 4 H100s for 3 days at $720-1,080 total. B200 reduces full SFT costs 25-35% versus H100 through 2x FP8 throughput and 192 GB VRAM reducing model parallelism overhead.
GPU COMPARISON
H200 offers 141 GB VRAM, fitting Maverick 72B LoRA on single GPU. B200's 192 GB enables Maverick 72B full SFT on 4 GPUs versus 8 H100s. B300's HBM4 and Vera CPU reduce full SFT time-to-train by 40-50% versus B200. For teams fine-tuning weekly, B200 saves $2,000-8,000/month versus H100 equivalent configurations.
OPTIMIZATION STRATEGIES
Use DeepSpeed ZeRO-3 with gradient checkpointing to reduce memory 30-50%. FlashAttention-3 accelerates long-context fine-tuning 2-3x. LoRA with rank 16-32 captures 90-95% of full FT performance at 5-10% of the cost. Pre-emptible spot instances for fine-tuning save 50-70% versus reserved with 90%+ completion rate for runs under 24 hours. For teams spending over $10,000/month on fine-tuning, reserved 12-month GPU contracts at 25-40% discount are cost-effective.