AllocateWhat is fine-tuning?
Fine-tuning continues a model’s training on your own examples so it learns your domain, formats, and decision patterns. A fine-tuned open-weight model typically beats a much larger general model on your specific task, at a fraction of the per-token cost, and the resulting weights can belong to you.
The inputs are pairs of task and outcome: resolved claims, cleared disputes, accepted answers. A few thousand high-quality examples usually move accuracy more than any prompt engineering.
On Allocate, fine-tuning runs against open-weight bases like Qwen 3.5, Llama 4 Scout, and GLM. The trained weights stay inside your boundary and belong to you; that ownership is the difference between renting intelligence and building an asset.
Explore fine-tunable models Try it: Fine-tuning cost calculatorRelated terms
Allocate is the cloud inference platform for companies that want to train and run their own models.