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Codesota · Tasks · React Native Code GenerationHome/Tasks/Mobile Development/React Native Code Generation

React Native Code Generation.

Evaluating AI models on generating correct, production-quality React Native implementations. Covers animation, navigation, state management, lists, and platform APIs using real-world libraries (Reanimated, React Navigation, Zustand, FlashList).

1
Datasets
40
Results
requirement-satisfaction
Canonical metric
§ 02 · Canonical benchmark

The reference dataset.

React Native Evals

A benchmark suite evaluating how AI coding models handle authentic React Native development tasks. 71 evals across 5 categories: animation (14), async-state management (14), lists (19), navigation (14), and React Native APIs (10). Each eval specifies explicit, judgeable requirements. Model outputs are scored on requirement satisfaction using LLM-based judging. Covers real libraries: Reanimated, React Navigation, Zustand, Jotai, React Query, FlatList, FlashList, LegendList.

Primary metric: requirement-satisfaction
View full leaderboard →
§ 03 · Top 10

Leading models.

Leading models on React Native Evals.

#Modelnavigation-satisfactionYearSource
Composer 298.92026paper ↗
2Composer 298.52026paper ↗
3Composer 296.22026paper ↗
4GPT 5.3 Codex95.62026paper ↗
5GPT-5.495.62026paper ↗
6Gemini 3.1 Pro94.42026paper ↗
7Composer 294.32026paper ↗
8Claude Opus 4.693.32026paper ↗
9Claude Sonnet 4.693.32026paper ↗
10Kimi K2.593.32026paper ↗

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§ 04 · All datasets

Tracked datasets.

1 dataset tracked for this task.

React Native Evals
CANONICAL
40 results · requirement-satisfaction
Top: Composer 2 98.9
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