AetherCode
Models write solutions to problems from premier programming contests such as IOI and ICPC. Expert-validated test suites judge each solution.
Test cases mix automatic generation with human curation to remove weak tests.
- Made by
- ByteDance Seed and collaborators (Wang et al.)
- Released
- August 2025
- Kind
- Competitive programming
- Level
- Competition
- Scored
- Checked automatically
- Answers
- Code
- Strongest model tested
- o4-mini #94 on the capability index
- Last in a launch post
- February 2026, dropped before it saturated
- Last model added
- June 2026
- Scores refreshed
- November 12th, 2026
In the authors’ words
Competitive programming has emerged as a critical benchmark for evaluating the reasoning and coding capabilities of Large Language Models (LLMs). Despite impressive progress on existing benchmarks, we argue that current evaluations overstate model proficiency, masking a substantial gap between LLMs and elite human programmers. This gap arises from two key limitations: insufficient difficulty and scope of benchmark problems, and evaluation bias from low-quality test cases. To address these shortcomings, we present AetherCode, a new benchmark that draws problems from premier programming competitions such as IOI and ICPC, offering broader coverage and higher difficulty. AetherCode further incorporates comprehensive, expert-validated test suites built through a hybrid of automated generation and human curation, ensuring rigorous and reliable assessment. By combining challenging problem design with robust evaluation, AetherCode provides a more faithful measure of LLM capabilities and sets a new standard for future research in code reasoning.
o4-mini leads with 35.5% among models released by September 2025
Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.
Seed2.1 Pro leads with 65.8%, claims included
Best score per model from every source, including labs’ own numbers and claims Epoch AI collected from reports and papers. Labs pick their own settings, so a claim can beat an independent run of the same model.
The newest model with a score here came out in September 2025, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon
- GPT-6 Astra
- Claude Opus 5.5
- and 16 more
- 35.5 o4-mini
- 32.7 Gemini-2.5-Pro [snapshot unspecified]
- 26.6 Seed-1.6-thinking-0715
- 22.3
DeepSeek-R1
- 20.3 Gemini-2.5-Flash [snapshot unspecified]
- 17.6
Qwen3-235B-A22B
- 16.3
Qwen3-32B
- 10.5 GPT-4.1
- 10.0
Qwen3-8B
- 9.80 Kimi K2
- 8.50
DeepSeek-V3
- 7.70
Qwen3-Coder-480B-A35B
- 4.40 GPT-4o [snapshot unspecified]
- 1 o4-mini high 35.5%
- 2 Gemini-2.5-Pro [snapshot unspecified] 32.7%
- 3 Seed-1.6-thinking-0715 26.6%
- 4
DeepSeek-R1 May 2025 22.3%
- 5 Gemini-2.5-Flash [snapshot unspecified] 20.3%
- 6
Qwen3-235B-A22B 17.6%
- 7
Qwen3-32B 16.3%
- 8 GPT-4.1 10.5%
- 9
Qwen3-8B 10%
- 10 Kimi K2 Sep 2025 9.80%
- 11
DeepSeek-V3 Mar 2025 8.50%
- 12
Qwen3-Coder-480B-A35B 7.70%
- 13 GPT-4o [snapshot unspecified] 4.40%
Source: Official AetherCode leaderboard
- 1
Seed2.1 Pro 65.8%
- 2
Seed2.0 Pro 60.6%
- 3
Seed1.8 38.2%
- 4 o4-mini high 35.5%
- 5
DeepSeek-R1 May 2025 22.3%
- 6
Qwen3-235B-A22B 17.6%
- 7
Qwen3-32B 16.3%
- 8 GPT-4.1 10.5%
- 9
Qwen3-8B 10%
- 10 Kimi K2 Sep 2025 9.80%
- 11
DeepSeek-V3 Mar 2025 8.50%
- 12
Qwen3-Coder-480B-A35B 7.70%
Sources: Labs’ model cards and official AetherCode leaderboard
| # | Entry | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | o4-mini | 35.5% | high | Apr 2025 | Official leaderboard |
| 2 | Gemini-2.5-Pro [snapshot unspecified] | 32.7% | Official leaderboard | ||
| 3 | Seed-1.6-thinking-0715 | 26.6% | Official leaderboard | ||
| 4 | | 22.3% | May 2025 | Official leaderboard | |
| 5 | Gemini-2.5-Flash [snapshot unspecified] | 20.3% | Official leaderboard | ||
| 6 | | 17.6% | Apr 2025 | Official leaderboard | |
| 7 | | 16.3% | Apr 2025 | Official leaderboard | |
| 8 | GPT-4.1 | 10.5% | Apr 2025 | Official leaderboard | |
| 9 | | 10% | Apr 2025 | Official leaderboard | |
| 10 | Kimi K2 Sep 2025 | 9.80% | Sep 2025 | Official leaderboard | |
| 11 | | 8.50% | Mar 2025 | Official leaderboard | |
| 12 | | 7.70% | Jul 2025 | Official leaderboard | |
| 13 | GPT-4o [snapshot unspecified] | 4.40% | Official leaderboard |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 65.8% | Jun 2026 | Lab model card | |
| 2 | | 60.6% | Feb 2026 | Lab model card | |
| 3 | | 38.2% | Dec 2025 | Lab model card | |
| 4 | o4-mini | 35.5% | high | Apr 2025 | Official leaderboard |
| 5 | | 22.3% | May 2025 | Official leaderboard | |
| 6 | | 17.6% | Apr 2025 | Official leaderboard | |
| 7 | | 16.3% | Apr 2025 | Official leaderboard | |
| 8 | GPT-4.1 | 10.5% | Apr 2025 | Official leaderboard | |
| 9 | | 10% | Apr 2025 | Official leaderboard | |
| 10 | Kimi K2 Sep 2025 | 9.80% | Sep 2025 | Official leaderboard | |
| 11 | | 8.50% | Mar 2025 | Official leaderboard | |
| 12 | | 7.70% | Jul 2025 | Official leaderboard |
Labs report scores for 3 models in their cards. Switch the scores above to rank them together.
Number one over time 4 models have held number one with claims included since its release in August 2025
Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for the benchmark’s own leaderboard and what labs claim in their cards.
Sources: Official AetherCode leaderboard and labs’ model cards
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Sources: Official AetherCode leaderboard and labs’ model cards
Labs headline it less often now, last in February 2026
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Feb 14, 2026 | 60.6 | AetherCode | |
| Dec 18, 2025 | 38.2 | AetherCode |
3 system cards report it, from 1 lab
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Jun 23, 2026 | | 65.8 | AetherCode (Table 11) | Capabilities |
| Mar 21, 2026 | | 38.2 | AetherCode (Table 1) | Capabilities |
| Feb 14, 2026 | | 60.6 | AetherCode (Table 3) | Capabilities |
More in Coding
- SWE-bench Verified In use 500 human-validated GitHub issues from 12 Python repos. Agent writes a patch that must pass hidden tests. Claude Opus 4.7 83.5%
- LiveCodeBench v6 In use Competitive programming problems collected after model cutoffs from LeetCode, AtCoder, Codeforces. Scored pass@1 on hidden tests.
DeepSeek-V4-Pro 93.5%
- SWE-bench Multilingual In use 300 GitHub-issue tasks across nine programming languages in SWE-bench format. Patch graded by repository tests. Claude Fable 5.2 96.6%
- DeepSWE In use 113 original long-horizon engineering tasks across 91 repos and five languages, written from scratch. Hand-written verifiers accept alternative solutions. GPT-6 Astra 74.1%
- SciCode In use Scientist-curated research coding problems split into subproblems across natural sciences. Code checked against test cases.
Seed2.1 Pro 59.8%
- Codeforces rating In use Model solves recent Codeforces contest problems. An Elo-style rating is computed from simulated contest performance.
DeepSeek V4.1 Flash 3,471