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Together AI Releases Together Compiler: Agents Make Inference Up to 2.6x Faster

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Together AI has introduced Together Compiler (TKCC), an agent-driven system that keeps re-optimizing inference as production traffic changes. Together Compiler already runs on several of Together’s serverless endpoints. The core claim for developers: an engine tuned once goes stale, so tuning should never stop. TL;DR System: It is an optimization system, tested on Kimi K3,

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Google AI Research Releases Agile Deliberation Framework for Gray-Area Image Classifiers

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Google Research has released Agile Deliberation, a human-in-the-loop framework for building image classifiers around subjective concepts. Think ‘healthy food’, ‘inspiring artwork’ or clickbait in content moderation. Most tooling assumes users already know the concept boundary. Agile Deliberation assumes they do not, and helps them find it. TL;DR Framework: It prompts Gemini 2.5 Pro and Gemini

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webAI Releases TwIL-8B, an 8.8B Reasoning Model Scoring 98.2 on MATH-500

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webAI has released TwIL-8B, an 8.8B reasoning model for math, code and instruction following. The TwIL-8B reasoning model is post-trained from IBM’s Granite 4.2 8B. Weights are on Hugging Face under a non-commercial license. webAI’s launch post frames the pitch around cost per task, not raw scale. The 4-bit build is 4.98 GiB, sized for

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Ricursive AI Releases Ripple-65B Preview: A 65B Dense Open-Weight Model Scoring 80.5 on Terminal-Bench 2.1

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Ricursive Intelligence just released Ripple-65B Preview. Ripple-65B Preview is a 65B dense open-weight model from Ricursive, pretrained from scratch for agentic coding. It is a general-purpose variant of the proprietary model behind Ricursive’s AI chip design platform. The main claim: 80.52 on Terminal-Bench 2.1, the top self-reported score among US open-weight models. Every MoE rival

Ricursive AI Releases Ripple-65B Preview: A 65B Dense Open-Weight Model Scoring 80.5 on Terminal-Bench 2.1 Read More »

Anthropic Releases FlashProve: Cryptographic Proofs That a Reply Came From Committed Weights

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Anthropic’s Frontier Red Team has released FlashProve, an open-source research prototype for provable inference. FlashProve is a zkSNARK system from Anthropic that proves a reply came from a committed model. The proof reveals nothing about the model weights. On Llama 4 Maverick, a 400B mixture-of-experts model, it proves about 110 tokens/second on 1 H100. For

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NVIDIA Shows 3 Ways to Speed Up MoE Inference on DGX Spark, Lifting Ling-3.0-flash Throughput 42.5%

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NVIDIA’s latest technical blog shows how to speed up mixture-of-experts (MoE) inference on one DGX Spark. The test model is Ant Group inclusionAI’s Ling-3.0-flash, a 124B-parameter MoE with 5.1B active parameters. NVIDIA stacked three optimizations: a new MoE kernel backend, an FP8 output layer and built-in speculative decoding. On all 1,319 GSM8K questions, decode throughput

NVIDIA Shows 3 Ways to Speed Up MoE Inference on DGX Spark, Lifting Ling-3.0-flash Throughput 42.5% Read More »

OpenAI Introduces Pando: A Git Backend That Cuts Median Push Latency ~80%

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OpenAI has introduced Pando, a new Git backend that now serves all development in its monorepo. The OpenAI Pando Git backend keeps the standard Git client and protocol. Engineers and Codex agents still run git push and git fetch as before. Only the server changed. OpenAI team reports median push latency fell nearly 80%. Pando

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Zyphra AI Introduces Zyphra Hierarchical Attention (ZHA): A Path to True Subquadratic Attention

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Zyphra has released Zyphra Hierarchical Attention (ZHA), a sparse attention method built around a tree-structured indexer. ZHA targets a known gap in sparse attention: the indexer that picks tokens still scans the whole context. Zyphra’s technical paper shows ZHA can be distilled into frozen pretrained models with about 4B tokens. On Qwen3.6-35B-A3B it stays close

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NVIDIA Releases Auto Ontology: An Open Semantic Layer That Grounds AI Agent SQL

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NVIDIA has released Auto Ontology, an open library under the Apache 2.0 license. NVIDIA Auto Ontology is a semantic layer framework that builds a context layer from enterprise metadata. Agents use that layer to write SQL against certified business definitions. The repository states the problem plainly: a fast revenue answer is worthless if the number

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Meet qwenGPU: Qwen3.5-2B With 45 Compiled GPU Layers That Run CUDA

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qwenGPU is an experimental model that compiles a SIMT GPU directly into the weights of Qwen3.5-2B. Developer Vixhal (@TheVixhal) released it on GitHub under the MIT license. The model runs real CUDA, compiled to NVIDIA PTX, inside its own forward passes. For developers, it tests one idea: exact computation inside a pretrained LLM, not beside

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