Models Are Getting Dumber on Purpose
Reasoning scores for AI models are increasing while per-token compute is decreasing. GLM-5.2 achieves 99.2% on AIME 2026 with 40 billion parameters, Qwen3.5 scores 91.3% with 17 billion parameters, and DeepSeek V4-Flash operates with 13 billion parameters, contrasting with GPT-4's rumored 280 billion parameters which struggled with AIME problems.
w4g1.dev
6 min
8/16/2026
The gap between open weights LLMs and closed source LLMs
A prediction indicates that a new Frontier Open Source LLM will be released on December 3, 2026. The analysis compares the performance gap between open weights and closed source LLMs by examining historical benchmarks.
blog.doubleword.ai
2 min
6/26/2026
Models Are Getting Dumber on Purpose
Reasoning scores for AI models are increasing while per-token compute is decreasing. GLM-5.2 achieves 99.2% on AIME 2026 with 40 billion parameters, Qwen3.5 scores 91.3% with 17 billion parameters, and DeepSeek V4-Flash operates with 13 billion parameters, contrasting with GPT-4's rumored 280 billion parameters which struggled with AIME problems.
w4g1.dev
6 min
8/16/2026
The gap between open weights LLMs and closed source LLMs
A prediction indicates that a new Frontier Open Source LLM will be released on December 3, 2026. The analysis compares the performance gap between open weights and closed source LLMs by examining historical benchmarks.
blog.doubleword.ai
2 min
6/26/2026
Models Are Getting Dumber on Purpose
Reasoning scores for AI models are increasing while per-token compute is decreasing. GLM-5.2 achieves 99.2% on AIME 2026 with 40 billion parameters, Qwen3.5 scores 91.3% with 17 billion parameters, and DeepSeek V4-Flash operates with 13 billion parameters, contrasting with GPT-4's rumored 280 billion parameters which struggled with AIME problems.
w4g1.dev
6 min
8/16/2026
The gap between open weights LLMs and closed source LLMs
A prediction indicates that a new Frontier Open Source LLM will be released on December 3, 2026. The analysis compares the performance gap between open weights and closed source LLMs by examining historical benchmarks.
blog.doubleword.ai
2 min
6/26/2026
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