---
title: "LLM Fine-Tuning"
description: "Fine-tune models on your codebase, conventions, and domain, so outputs match how your teams actually build."
url: https://www.callstack.com/services/llm-fine-tuning
updated: 2026-11-09T15:58:27.290Z
---

# LLM Fine-Tuning

Fine-tune models on your codebase, conventions, and domain, so outputs match how your teams actually build.

_[Agentic Delivery](/agentic-delivery) › [Custom & Private Models](/capabilities/custom-private-models)_

**A model that writes code like your team**

Generic models write generic code. We fine-tune models on your codebase, conventions, and domain - the same capability behind Apex, our specialized React Native model - so outputs match how your teams actually build.

## Custom & Private Models

- 30/31 Next.js tasks as pixel canary · 85% Lower inference cost vs Opus 5.5
- Industry runs on our tooling · 50M+ OSS downloads / month
- 100+ Enterprise projects delivered
- React Foundation Founding Member · 300+ commits to React Native · Contributing since 2016
- ISO 27001 certified
- 32 Models tested against React Native

## What you get: Specialization that pays.

- **Training data pipeline** Data curated from your repos, reviews, and docs, with licensing and privacy checks.
- **Task-focused tuning** LoRA and full fine-tunes aimed at the workflows that matter, not vanity benchmarks.
- **Rigorous evaluation** Improvements proven on held-out, real-task evals before rollout.
- **Deployment flexibility** Tuned models served in your cloud, on-premise, or on-device.
- **Cost-efficiency gains** Smaller specialized models beating larger generic ones on your tasks, at a fraction of the cost.
- **Refresh process** A re-tuning cadence as your codebase and conventions evolve.

## Scope → Build → Scale: Deploy models where the workload fits.

### Scope (1 WEEK)
We select a product workflow, define where agents act, and agree the controls and success measures.
- Workflow and owners defined
- Baseline and controls agreed
- Token budgets confirmed
### Build (1-12 MONTHS)
We connect context, agents, and verification to your tools, then run the workflow on your product backlog.
- Running on your product backlog
- Speed and quality measured
- Business impact validated
### Scale (AS NEEDED)
We document the workflow, transfer ownership, and extend it across teams and products based on results.
- Your team owns the workflow
- Expand based on results
- Full knowledge handover

**Stop prompting around the gap.** A model specialized to your stack, proven on your tasks. [Plan my model strategy](/contact)

> Their engineers proved to be a crucial part of our mobile app relaunch project.
>
> — Brian Aznar, Engineering Director, Major League Soccer

We’ll connect you with the right expert within 24 hours.

## Let’s find the right path for your product.

**When is fine-tuning worth it versus prompting or retrieval?**

When prompting plateaus: persistent style mismatches, domain language the model lacks, or cost pressure at volume. We check the cheaper levers first and say so if they suffice.
**How much data do we need?**

Less than most expect. Thousands of quality examples move behavior; we build the dataset from your repos and review history with curation, not bulk export.
**Which base models do you tune?**

Open-weight models chosen by evaluation on your tasks - the same discipline we used building Apex, our React Native coding model.
**Who owns the resulting model?**

You do: weights, dataset, and evaluation harness. No per-seat licensing on your own model.
**How long does a fine-tuning cycle take?**

Weeks end to end: dataset construction, tuning runs, evaluation, and deployment. Refreshes are faster once the pipeline exists.
**How do we know it is actually better?**

Held-out evaluations on your real tasks, compared against the base model and hosted alternatives. If the tuned model does not win, we tell you.

## Open source

- [React Native AI](https://github.com/callstackincubator/ai): On-device LLM execution in React Native with Vercel AI SDK compatibility
- [React Native Evals](https://github.com/callstackincubator/evals): A benchmark suite for evaluating how coding models solve real React Native tasks
- [Skill Gym](https://incubator.callstack.com/skillgym/): Prove your agent skills work before you ship them