C3-Bench (Controllable Code Completion) - Scale Control: leaderboard

C3-Bench's Scale-Control task (Alibaba Group with USTC, UCAS and CASIA, 2026): given the Python code around a missing segment, a model must complete exactly the requested scope, such as the rest of a partial line, a set number of lines or one if, for or while block, over 909 tasks built from HumanEval and SAFIM. Completions are checked automatically by AST node type and line count, with no unit tests; the score is the percentage that match the requested scope, higher is better. Base code models are prompted in fill-in-the-middle token format and chat models in a ChatML template, and the authors' Qwen2.5-Coder-C3 models are fine-tuned on synthetic data in this task format.

Metric: Instruction-Following Rate (%; 909 SCC tasks: AST node-type and line-count check of the requested completion scope). Source: arxiv.org. Saturation forecast: Estimated already saturated. 42 models tracked.

Top models

#ModelScoreOverall rank
1O1 (2024-12-17)59.6#310
2Claude 3.5 Sonnet (20241022)50.8#635
3O1 Preview48.9#483
4O1 Mini44.7#761
5Claude 3.5 Haiku26.4#1563
6GPT-4o (2024-08-06)24.1#731
7GPT-4o (2024-11-20)24.1#864
8GPT-4o Mini (2024-07-18)22.5#1512
9GPT-4o (2024-05-13)20.8#734
10DeepSeek V320.2#705
11DeepSeek V3 (0324)20.2#704
12Qwen 2.5 Coder 32B Instruct16.9#1553
13Qwen 2.5 Coder 3B Instruct14.2#3610
14Qwen 2.5 Coder 14B Instruct13.5#1843
15Qwen 2.5 72B Instruct9.4#1093

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=c3-bench-controllable-code-completion-scale-control · How It Works · Data refreshed daily, snapshot 2026-11-12.