STEM & Reasoning Benchmark

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.

Model scores 37 models tested

Reset
# Model Score Date Source Verified
1 DeepSeek-V4-Pro
DeepSeek
93.5%
26.06.2026 Report Verified
2 DeepSeek-V4-Pro
DeepSeek
92.5%
04.06.2026 Report Unverified
3 Qwen3.8-Flash-Next
Qwen Team (Alibaba)
91.9%
26.08.2026 Report Verified
4 DeepSeek-V4-Flash
DeepSeek
91.6%
26.06.2026 Report Verified
5 DeepSeek-V4-Flash-0731
DeepSeek
90.6%
26.08.2026 Report Unverified
6 Qwen3.8-27B
Qwen Team (Alibaba Cloud)
90.3%
18.08.2026 Report Verified
7 Kimi K2.6
Moonshot AI
90.2%
04.06.2026 Report Unverified
8 Bonsai 2 27B — GGUF
Prism ML
90.07%
17.09.2026 Report Verified
9 NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16
NVIDIA
89%
04.06.2026 Report Verified
10 Kolibri-1
Aleph Alpha
85.9%
03.10.2026 Report Verified
11 Kimi K2.5
Moonshot AI
85%
23.08.2026 Report Verified
12 Qwen3.6-27B
Qwen Team (Alibaba Cloud)
83.9%
22.04.2026 Qwen Team (official model card) Verified
13 Raon-1 mini
KRAFTON AI
81.6%
21.10.2026 Report Verified
14 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
80.7%
16.04.2026 Qwen Team (official model card - comparison) Unverified
15 Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
80.4%
16.04.2026 Qwen Team (official model card); KRAFTON re-eval (Raon-1-mini-preview card, gpt-5.6-luna harness): 81.2 Verified
16 Gemma4-31B-it
Google
80%
16.04.2026 Qwen Team (official model card - comparison) Unverified
17 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
78.9%
01.02.2026 Report Verified
18 Muse-Glimmer-30B
Meta Superintelligence Lab
77.4%
21.10.2026 Report Unverified
19 Gemma4-26B-A4B
Google
77.1%
16.04.2026 Qwen Team (official model card - comparison); KRAFTON re-eval (Raon-1-mini-preview card, gpt-5.6-luna harness): 83.4 Unverified
20 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
75.1%
01.02.2026 Report Unverified
21 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
74.6%
16.04.2026 Qwen Team (official model card - comparison) Unverified
22 LFM3-1.7B
LiquidAI
73.46%
— Report Verified
23 Gemma4-12B
Google
72%
02.07.2026 Report Verified
24 MiniCPM5-2B
OpenBMB
69.1%
— Report Verified
25 Qwen3-Next-80B-A3B-Thinking
Qwen
68.7%
10.09.2025 Report Verified
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What now?

You've seen how models score on LiveCodeBench v6 — here's what to do next.