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Three new papers expose systematic VLM failures on basic physics, introduce RL that learns to abandon bad reasoning paths, and reveal that AI agents deceive primarily through misdirection rather than fabrication.
Grok 4 is xAI's frontier reasoning model, the first to break 50% on Humanity's Last Exam, with a 256K context window, $3/M input pricing, and a Heavy multi-agent variant built on 200,000 GPUs.
OpenAI's CoT-Control benchmark shows frontier reasoning models score 0.1-15.4% at steering their own chain of thought - a result the company frames as good news for AI oversight.
New research shows reasoning models can't suppress their chain-of-thought, that they commit to answers internally long before their CoT reveals it, and that static benchmarks are inadequate for measuring real-world agent adaptability.
A community fine-tune distills Claude Opus 4.6 chain-of-thought reasoning into Qwen3.5-27B via LoRA, racking up 4,000+ downloads in days. No benchmarks yet - but the approach raises familiar questions.
Community fine-tune that distills Claude Opus 4.6 reasoning into Qwen3.5-27B via LoRA. 28B parameters, Apache 2.0, no published benchmarks.
Comparing the Claude Opus reasoning-distilled Qwen3.5-27B against the base model - what chain-of-thought distillation adds and what it costs in context, multimodal, and reliability.
Microsoft releases Phi-4-reasoning-vision-15B - a 15B open-weight multimodal model trained on 240 GPUs in 4 days that competes with 100B+ parameter models on math, science, and GUI understanding.
GPT-5.4 leads on computer use and enterprise productivity. Gemini 3.1 Pro leads on science reasoning and math at 20% lower cost. A benchmark-by-benchmark comparison.
OpenAI's most capable frontier model combines native computer use, 1M-token context, and three variants at $2.50/$15 per million tokens.
Claude Code 2.1.68 restores the ultrathink keyword after community backlash over quality degradation, while setting Opus 4.6 to medium effort by default for speed on daily tasks.
Three new papers tackle reasoning efficiency, agent vulnerability to web misinformation, and error correction in multi-step AI workflows.
