And MIT License, as always. More on reddit.com

It finally manages to think in languages other than English, and the second model to pass my native language poetry test, after gemini 2.5 pro More on reddit.com

The lack of sleep due to the never ending stream of new and better models may be lethal. More on reddit.com

Those benchmarks are a meme. ArtificialAnalysis uses benchmarks established by other research groups, which are often old and overtrained, so they aren't reliable. They carefully show or hide models on default list to paint a picture of bigger models doing better, but when you enable Qwen 8B and 32B with reasoning to be shown, this all falls apart. It's nice enough to brag about a model on LinkedIn, and they are somewhat useful - they seem to be independent and the image and video arenas are great, but they're not capable of maintaining a leak-proof expert benchmarks. Look at math reasoning: DeepSeek R10528 (May '25) - 94 Qwen3 14B (reasoning) - 86 Qwen3 8B (Reasoning) - 83 DeepSeek R1 (Jan '25) - 82 DeepSeek R1 05-28 Qwen3 8B - 79 Claude 3.7 Sonnet (thinking) - 72 Overall bench (Intelligence Index) : DeepSeek R1 (Jan '25) - 60 Qwen3 32B (Reasoning) - 59 Do you believe that it makes sense for Qwen3 8B to score above DeepSeek R1 or for Claude Sonnet 3.7 to be outclassed by DeepSeek R1 05-28 Qwen3 8B with a big margin? Another bench - LiveCodeBench Qwen3 14B (Reasoning) - 52 Claude 3.7 Sonnet thinking - 47 Why are devs using Claude 3.7/4 in Windsurf/Cursor/Roo/Cline/Aider and not Qwen 3 14B? Qwen3 14B is apparently a much better coder lmao. I can't call it benchmark contamination but it's definitely overfit to benchmarks. For god's sake, when you let base Qwen 2.5 32B non-Instruct generate random tokens with trash prompt it will often generate MMLU-style questions and answer pairs out of itself. It's trained to do well at benchmarks that they test on. More on reddit.com