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Person: "willccbb"
xAI Grok 4.1: #1 in Text Arena, #1 in EQ-bench, and better Creative Writing
grok-4.1 gpt-5.1 claude-4.1-opus grok-4 gpt-5 grok-4.1-thinking gpt-5-pro claude-4.5-haiku xai openai google-deepmind sakana-ai anthropic microsoft mufg khosla nea lux-capital iqt model-performance creative-writing hallucination evaluation-datasets ensemble-models weather-forecasting funding efficiency anti-hallucination arc-agi model-scaling yanndubs gregkamradt philschmid willccbb
xAI launched Grok 4.1, achieving a #1 rank on the LM Arena Text Leaderboard with an Elo score of 1483, showing improvements in creative writing and anti-hallucination. OpenAI's GPT-5.1 "Thinking" demonstrates efficiency gains with ~60% less "thinking" on easy queries and strong ARC-AGI performance. Google DeepMind released WeatherNext 2, an ensemble generative model that is 8× faster and more accurate for global weather forecasts, integrated into multiple Google products. Sakana AI raised ¥20B ($135M) in Series B funding at a $2.63B valuation to focus on efficient AI for resource-constrained enterprise applications in Japan. New evaluations highlight tradeoffs between hallucination and knowledge accuracy across models including Claude 4.1 Opus and Anthropic models.
Cohere Command A Reasoning beats GPT-OSS-120B and DeepSeek R1 0528
command-a-reasoning deepseek-v3.1 cohere deepseek intel huggingface baseten vllm-project chutes-ai anycoder agentic-ai hybrid-models long-context fp8-training mixture-of-experts benchmarking quantization reasoning coding-workflows model-pricing artificialanlys reach_vb scaling01 cline ben_burtenshaw haihaoshen jon_durbin _akhaliq willccbb teortaxestex
Cohere's Command A Reasoning model outperforms GPT-OSS in open deep research capabilities, emphasizing agentic use cases for 2025. DeepSeek-V3.1 introduces a hybrid reasoning architecture toggling between reasoning and non-reasoning modes, optimized for agentic workflows and coding, with extensive long-context pretraining (~630B tokens for 32k context, ~209B for 128k), FP8 training, and a large MoE expert count (~37B). Benchmarks show competitive performance with notable improvements in SWE-Bench and other reasoning tasks. The model supports a $0.56/M input and $1.68/M output pricing on the DeepSeek API and enjoys rapid ecosystem integration including HF weights, INT4 quantization by Intel, and vLLM reasoning toggles. Community feedback highlights the hybrid design's pragmatic approach to agent and software engineering workflows, though some note the lack of tool use in reasoning mode.