Trae Code Gen

Progress Over Time

Interactive timeline showing model performance evolution on Trae Code Gen

State-of-the-art frontier
Open
Proprietary

Trae Code Gen Leaderboard

2 models
ContextCostLicense
1
ByteDance
ByteDance
2
ByteDance
ByteDance
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About this benchmark

What is Trae Code Gen?

Trae Code Gen is a component of Trae Agent Bench that evaluates implementing new functionality across multiple programming languages in containerized, runnable repositories.

Trae Code Gen is a text benchmark evaluating models on agents and coding tasks. LLM Stats tracks 2 models on this benchmark, scored on a 0–1 scale. The current average is 0.6, with the leader at 0.6.

Compare leaders on the best AI for agents and best AI for coding leaderboards.

Current leaders

Seed 2.1 Pro from ByteDance currently leads the Trae Code Gen leaderboard with a score of 0.624 across 2 evaluated AI models.

1Seed 2.1 ProByteDance62.4%
2Seed 2.1 TurboByteDance59.7%

FAQ

Common questions about the Trae Code Gen benchmark and leaderboard.

What is the Trae Code Gen benchmark?

Trae Code Gen is a component of Trae Agent Bench that evaluates implementing new functionality across multiple programming languages in containerized, runnable repositories.

What is the Trae Code Gen leaderboard?

The Trae Code Gen leaderboard ranks 2 AI models based on their performance on this benchmark. Currently, Seed 2.1 Pro by ByteDance leads with a score of 0.624. The average score across all models is 0.611.

What is the highest Trae Code Gen score?

The highest Trae Code Gen score is 0.624, achieved by Seed 2.1 Pro from ByteDance.

How many models are evaluated on Trae Code Gen?

2 models have been evaluated on the Trae Code Gen benchmark, with 0 verified results and 2 self-reported results.

What categories does Trae Code Gen cover?

Trae Code Gen is categorized under agents and coding. The benchmark evaluates text models with multilingual support.

How recent are the Trae Code Gen leaderboard results?

The Trae Code Gen leaderboard was last updated in June 2026 and currently includes 2 evaluated models.