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Topic: "inference-efficiency"
GPT-5 Codex launch and OpenAI's quiet rise in Agentic Coding
gpt-5-codex qwen3-next-80b openai alibaba together-ai nvidia agentic-ai software-engineering long-context mixture-of-experts model-optimization cuda-acceleration inference-efficiency routing task-adaptive-thinking sama swyx omarsar0 ofirpress
OpenAI released GPT-5-Codex, an agentic coding model optimized for long-running software engineering tasks with dynamic task-adaptive thinking, multi-hour autonomy, and improved code quality. It achieves 51% accuracy on an unreleased large refactor benchmark and integrates deeply with developer tools like Xcode. Meanwhile, Alibaba launched Qwen3-Next-80B, a hybrid MoE model with native long-context support (262k tokens, extensible to 1M+), targeting efficient reasoning and repository-scale code analysis, supported by Together AI and NVIDIA with CUDA-accelerated attention. The trend towards hybrid SSM + MoE architectures is noted, emphasizing efficiency and scaling in China and US training regimes. Community discussions highlight the importance of variable compute and routing for inference efficiency and quality.
Cursor @ $9b, OpenAI Buys Windsurf @ $3b
llama-nemotron-ultra llama-nemotron-super llama-nemotron-nano qwen3-235b-a22b prover-v2 phi-4-reasoning ernie-4.5-turbo ernie-x1-turbo suno-v4.5 gen-4-references o1-mini openai cursor nvidia alibaba deepseek microsoft baidu suno runway keras reasoning inference-efficiency open-license moe-models math-reasoning theorem-proving model-performance music-generation image-generation recommender-systems tpu-optimization _akhaliq adcock_brett lmarena_ai fchollet
OpenAI is reportedly close to closing a deal with Windsurf, coinciding with Cursor's $900M funding round at a $9B valuation. Nvidia launched the Llama-Nemotron series featuring models from 8B to 253B parameters, praised for reasoning and inference efficiency. Alibaba released the Qwen3 family with MoE and dense models up to 235B parameters, ranking highly in coding and math benchmarks. DeepSeek introduced Prover-V2, an open-source AI for math reasoning with an 88.9% pass rate on MiniF2F-test. Microsoft released reasoning-focused Phi-4 models, outperforming OpenAI's o1-mini. Baidu debuted turbo versions of ERNIE 4.5 and X1 for faster, cheaper inference. Suno v4.5 added advanced AI music generation features, while Runway Gen-4 References enable placing characters into scenes with high consistency. KerasRS, a new recommender system library optimized for TPUs, was released by Fran ois Chollet.
Common Corpus: 2T Open Tokens with Provenance
qwen-2.5-coder claude-3.5-sonnet janusflow-1.3b ocronos-vintage pleais huggingface langchainai deepseek alibaba anthropic provenance ocr multilingual-datasets prompt-engineering multimodality image-generation code-generation quantization model-scaling inference-efficiency tim-dettmers tom-doerr omarsar0 swyx madiator reach_vb
Pleais via Huggingface released Common Corpus, the largest fully open multilingual dataset with over 2 trillion tokens including detailed provenance information. They also introduced OCRonos-Vintage, a 124M-parameter OCR correction model that efficiently fixes digitization errors on CPU and GPU, unlocking knowledge from PDFs. On AI tools, LangChainAI launched Prompt Canvas for collaborative prompt engineering, while DeepSeek released JanusFlow 1.3B, a unified multimodal LLM integrating autoregressive and rectified flow models for enhanced image understanding and generation. Alibaba Cloud announced Qwen2.5-Coder, a code-focused LLM with advanced coding capabilities, and Claude 3.5 Sonnet was highlighted for superior code generation. Discussions on quantization challenges and scaling laws for precision by Tim Dettmers and others emphasized the impact of low-precision training on model scalability and inference efficiency. "Scaling Laws for Precision" paper insights and alternative efficiency methods were also noted.