| Rank | Model | Score |
|---|---|---|
| 1 | seed-2-1-turbo | 0.679 |
| 2 | seed-2-1-pro | 0.658 |
| 3 | o4-mini-high | 0.355 |
| 4 | gemini-2-5-pro | 0.327 |
| 5 | seed-1-6-thinking | 0.266 |
| 6 | deepseek-r1-0528 | 0.223 |
| 7 | gemini-2-5-flash | 0.203 |
| 8 | qwen3-235b-a22b | 0.176 |
| 9 | qwen3-32b | 0.163 |
| 10 | gpt-4-1 | 0.105 |
| 11 | qwen3-8b | 0.1 |
| 12 | kimi-k2-instruct | 0.098 |
| 13 | deepseek-v3-0324 | 0.085 |
| 14 | qwen3-coder-480b-a35b | 0.077 |
| 15 | gpt-4o | 0.044 |
1 phaseActive
ByteDance's olympiad-level competitive programming benchmark testing advanced algorithmic reasoning and code synthesis. Metric: 0–1 score.
Quick answer: AetherCode is ByteDance's benchmark of olympiad-level competitive programming problems from IOI/ICPC contests, testing LLMs on advanced algorithmic reasoning and code synthesis. Best Pass@1: 35.5% (o4-mini-high, 2025). Even top models solve fewer than 40% of problems.
What it tests: An LLM's ability to solve hard algorithmic coding problems drawn from competitive programming contests — requiring mastery of data structures, graph algorithms, dynamic programming, number theory, and combinatorics.
Why it matters: Standard coding benchmarks (HumanEval, MBPP, LiveCodeBench) have saturated for frontier models. AetherCode's olympiad-difficulty floor creates meaningful separation between models that can reason through complex multi-step algorithmic problems and those that cannot, making it relevant for evaluating state-of-the-art reasoning-heavy code generation.
Known limitations: No paper or public dataset is available as of mid-2026, limiting independent reproduction and analysis. With only 2 models tracked publicly, leaderboard coverage is sparse.
AetherCode focuses on the highest tier of coding difficulty: problems from programming olympiads, where solutions require not just syntactically correct code but deep algorithmic insight. Unlike benchmarks built from interview-style questions or library usage tasks, olympiad problems demand that a model understand and apply non-trivial algorithms correctly under problem-specific constraints.
The benchmark evaluates whether a model can derive the correct algorithmic approach, implement it efficiently, and handle edge cases — all in a single pass without interactive debugging. This makes it a direct measure of end-to-end algorithmic problem-solving rather than code autocomplete or library API recall.
Scores are reported on a 0–1 scale, reflecting the fraction of problems solved correctly.
| Field | Value |
|---|---|
| Task category | Competitive programming / Coding |
| Metric | Score (0–1) |
| Difficulty | Olympiad level |
| Languages | English |
| Saturation | Low |
| Created by | ByteDance |
| Paper | Not yet public |
| GitHub | Not yet public |
| Dataset | Not yet public |
Models are evaluated by executing their generated code against hidden test cases for each problem. A problem is marked correct only if the solution passes all test cases. The aggregate score is the fraction of problems solved, reported on a 0–1 scale where 1.0 means all olympiad problems solved correctly.
No Benchgen results yet — be the first to run AetherCode.
| Benchmark | What it tests | Difficulty | Saturation |
|---|---|---|---|
| AetherCode | Olympiad competitive programming | Highest | Low |
| LiveCodeBench Pro | Competitive programming (continuous) | Very high | Low |
| SWE-Bench Pro | Real-world software engineering | High | Low |
| SciCode | Scientific research coding | High | Low |
AetherCode sits at the hardest end of the coding difficulty spectrum alongside LiveCodeBench Pro. Use AetherCode when you need to differentiate frontier models on pure algorithmic reasoning; use SWE-Bench Pro when production engineering tasks matter more.
Benchgen lets you run AetherCode against your own model checkpoints and track performance across fine-tuning runs, catching regressions in algorithmic reasoning before they reach production. Version-controlled benchmark results replace one-off comparisons with a continuous quality signal.
AetherCode is a competitive programming benchmark from ByteDance that evaluates LLMs on olympiad-level algorithmic coding problems. It targets the hardest tier of code generation, requiring mastery of advanced data structures and algorithms.
Scores are reported on a 0–1 scale. As of mid-2026, the highest publicly tracked score is 0.679 (Seed 2.1 Turbo), indicating the benchmark remains well below saturation and that even frontier models solve fewer than 70% of olympiad problems.
AetherCode was created by ByteDance. No public paper or dataset has been released as of mid-2026.