LiveCodeBench v6
LiveCodeBench v6 - competitive programming evaluation with latest problems.
Category
STEM & Reasoning
Score type
percent
Scale
100%
higher is better
Models tested
37
What is LiveCodeBench v6?
LiveCodeBench v6 is a continuously refreshed competitive programming benchmark: it collects problems from Codeforces, AtCoder and LeetCode by publication date, so the model can never memorise the answers from training data. v6 is the edition with the newest problem window (2025).
What does it test?
LiveCodeBench v6 measures hard reasoning in science, technology, engineering and math. In detail, it checks:
- competitive programming with correct solutions
- no contamination: only problems newer than the model's cutoff
- pass@1 on executable, test-based tasks
- algorithmic skill across contest platforms
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Frequently asked questions
What is the LiveCodeBench v6 benchmark?
LiveCodeBench v6 is a continuously refreshed competitive programming benchmark: it collects problems from Codeforces, AtCoder and LeetCode by publication date, so the model can never memorise the answers from training data. v6 is the edition with the newest problem window (2025).
What does LiveCodeBench v6 test?
LiveCodeBench v6 mainly measures hard reasoning in science, technology, engineering and math. Concretely, it checks: competitive programming with correct solutions; no contamination: only problems newer than the model's cutoff; pass@1 on executable, test-based tasks.
How is the LiveCodeBench v6 score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get LiveCodeBench v6 data and scores?
The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/livecodebench-v6/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Benchmark dataset
The question/task data itself — download and evaluate locally
Benchmark metadata (JSON)
This page's benchmark record from the Open LLM Radar API
All model scores (JSON download)
Full score table as JSON; paginate with limit/offset params
Open LLM Radar API docs
Swagger UI to explore and reuse all radar API endpoints
Model scores 37 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 26 |
Qwen3-30B-A3B-Thinking-2507
Qwen
|
66%
|
31.07.2025 | Report | Verified |
| 27 |
granite-4.2-3B
IBM
|
58.9%
|
— | Report | Verified |
| 28 |
Qwen3-30B-A3B
Qwen
|
57.4%
|
29.04.2025 | Report | Verified |
| 29 |
Qwen3.5-4B
Qwen
|
55.8%
|
01.02.2026 | Report | Verified |
| 30 |
Gemma4-E4B
Google
|
52%
|
02.07.2026 | Report | Verified |
| 31 |
Nemotron-3-Nano-4B
NVIDIA
|
50.7%
|
— | Report | Verified |
| 32 |
Gemma4-E2B
Google
|
44%
|
02.07.2026 | Report | Verified |
| 33 |
Qwen3-VL-30B-A3B
Qwen
|
42.6%
|
04.10.2025 | Report | Verified |
| 34 |
LFM2.5-2.6B
LiquidAI
|
42.1%
|
— | Report | Verified |
| 35 |
LFM2.5-8B-A1B
LiquidAI
|
39.8%
|
— | Report | Verified |
| 36 |
Gemma3-27B
Google
|
29.1%
|
02.07.2026 | Report | Unverified |
| 37 |
Qwen3.5-2B
Qwen Team (Alibaba Cloud)
|
20.2%
|
— | Report | Verified |