BlogLLM Benchmark Scores as Published, Side by Side

OJBench: Results as Published

Every result the catalog holds for OJBench: 24 models from 6 developers, read from 5 pages. Each number is as printed by the company named beside it; nothing is ranked or rescored. Models are listed by developer, newest first.

Area Code GenerationMaintainer Zhexu Wang and co-authorsIntroduced 2025Data version 2026103001, as of 2026-10-30

OJBench tests competition-level programming. It has 232 problems from China's National Olympiad in Informatics and the International Collegiate Programming Contest, together with the test cases released by the organizers. A model may answer in Python or CPP. A solution is correct only if it passes every test case, and the reported metric is Pass@n, which counts a problem as passed when at least one of n solutions is correct.

OJBench (language not stated)

ModelValuePrinted bySetup as printed
GPT-5 miniOpenAI, released 2025-08-0740.4%Alibaba, Qwen3.5-122B-A10B model cardchecked 2026-10-15-
gpt-oss-120bOpenAI, released 2025-08-0541.5%Alibaba, Qwen3.5-122B-A10B model cardchecked 2026-10-15-
GPT-4.1OpenAI, released 2025-04-1419.5%Moonshot AI, Kimi K2 release pagechecked 2026-10-15-
Claude Opus 4Anthropic, released 2025-05-2219.6%Moonshot AI, Kimi K2 release pagechecked 2026-10-15Effort: no extended thinking
Claude Sonnet 4Anthropic, released 2025-05-2215.3%Moonshot AI, Kimi K2 release pagechecked 2026-10-15Effort: no extended thinking
Gemini 2.5 FlashGoogle, released 2025-05-2019.5%Moonshot AI, Kimi K2 release pagechecked 2026-10-15-
DeepSeek-V3-0324DeepSeek, released 2025-03-2424%Moonshot AI, Kimi K2 release pagechecked 2026-10-15-
Qwen3.5-122B-A10BAlibaba, released 2026-02-2439.5%Alibaba, Qwen3.5-122B-A10B model cardchecked 2026-10-15-
Qwen3.5-27BAlibaba, released 2026-02-2440.1%Alibaba, Qwen3.5-122B-A10B model cardchecked 2026-10-15-
Qwen3.5-35B-A3BAlibaba, released 2026-02-2436%Alibaba, Qwen3.5-122B-A10B model cardchecked 2026-10-15-
Qwen3-235B-A22BAlibaba, released 2025-04-2932.7%Alibaba, Qwen3.5-122B-A10B model cardchecked 2026-10-15; printed on 1 more page-
Kimi K2 InstructMoonshot AI, released 2025-07-1127.1%Moonshot AI, Kimi K2 release pagechecked 2026-10-15-

OJBench (C++)

ModelValuePrinted bySetup as printed
GPT-5OpenAI, released 2025-08-0756.2%Moonshot AI, Kimi K2 Thinking release pagechecked 2026-10-15Effort: high; Tools: none
Claude Opus 4.5Anthropic, released 2025-11-2454.6%Moonshot AI, Kimi K2.5 model cardchecked 2026-10-15-
Claude Sonnet 4.5Anthropic, released 2025-09-2930.4%Moonshot AI, Kimi K2 Thinking release pagechecked 2026-10-15Effort: thinking; Tools: none
Gemini 3 ProGoogle, released 2025-11-1868.5%Moonshot AI, Kimi K2.5 model cardchecked 2026-10-15Effort: high
DeepSeek-V3.2DeepSeek, released 2025-12-0154.7%Moonshot AI, Kimi K2.5 model cardchecked 2026-10-15-
DeepSeek-V3.2-ExpDeepSeek, released 2025-09-2938.2%Moonshot AI, Kimi K2 Thinking release pagechecked 2026-10-15Tools: none
Kimi K2.5Moonshot AI, released 2026-01-2757.4%Moonshot AI, Kimi K2.5 model cardchecked 2026-10-15-
Kimi K2 ThinkingMoonshot AI, released 2025-11-0648.7%Moonshot AI, Kimi K2 Thinking release pagechecked 2026-10-15Effort: thinking; Tools: none
Kimi K2 Instruct 0905Moonshot AI, released 2025-09-0525.5%Moonshot AI, Kimi K2 Thinking release pagechecked 2026-10-15Tools: none

OJBench (Python)

ModelValuePrinted bySetup as printed
Claude Opus 4.6Anthropic, released 2026-02-0560.3%Moonshot AI, Kimi K2.6 model cardchecked 2026-10-15Effort: max
Gemini 3.1 Pro PreviewGoogle, released 2026-02-1970.7%Moonshot AI, Kimi K2.6 model cardchecked 2026-10-15Effort: high
Kimi K2.6Moonshot AI, released 2026-04-2060.6%Moonshot AI, Kimi K2.6 model cardchecked 2026-10-15-
Kimi K2.5Moonshot AI, released 2026-01-2754.7%Moonshot AI, Kimi K2.6 model cardchecked 2026-10-15-

Every number here is read from the same catalog file as the benchmark table, data version 2026103001, and is the number the table shows for that model and test. Where one page printed a model under several setups, each value is listed. The catalog is public in armanobosyan/sugra-llm-benchmarks; a wrong number can be reported from the table, with Report an error under the value, or as an issue in that repository.