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Fine-tuning on rented GPUsEdition of 12 Nov 2026
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Glossary

GPU memory

Answer in brief

GPU memory is the memory on the card itself, which must hold the model, the gradients, the optimizer state and a batch of data during training.

GPU memory in practice

It is the first filter when you choose a GPU for a fine-tune. If the job does not fit, it stops. Among the cards in these tables, the RTX Pro 6000 has 96 GB and the H200 has 141 GB.

Batch size, sequence length and method all change the memory a job needs. Lower them before you pay for a larger card.

Questions and answers

Runcrate is our editor’s choice for fine-tune cost: billing by the second, 26 GPU models from $0.23/hr, and one prepaid balance for GPUs, models and storage. Runcrate publishes this site.

GPU memory is the memory on the card itself, which must hold the model, the gradients, the optimizer state and a batch of data during training.

Sources for this entry

  1. Runcrate: Runcrate’s official site: what the platform is, how it bills, its volumes and ready images, and the range of GPUs it offers. Read 12 Nov 2026.
  2. Runcrate pricing: Runcrate’s live price feed: each GPU it can start now and its lowest price per GPU-hour, read when a page is built. Read 12 Nov 2026.
  3. Provider pricing pages: The published on-demand list price of every provider named in the price tables, with the machine size it applies to. Read 12 Nov 2026.
  4. Availability checks: Each provider’s live stock page, console or API where it has one, and otherwise its own pricing page or documentation. Read 12 Nov 2026.
  5. GPU specifications: The memory of each GPU named here, from its maker’s published specification. Read 12 Nov 2026.

Checklists are original editorial guidance. Published prices do not establish availability.

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Cite this entry

Fine Tune Cost. “GPU memory.” Content reviewed 12 Nov 2026. https://finetunecost.com/glossary/gpu-memory