Qwen3.5 news
The latest Qwen3.5 news, : Google TPUv7 outperforms NVIDIA GPUs in agentic inference benchmarks.
6 stories mentioning Qwen3.5 since 25 September 2026, newest first, each with its sources and discussion. Follow to see new ones on your front page.
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Google TPUv7 outperforms NVIDIA GPUs in agentic inference benchmarks
Google’s TPUv7 chip has demonstrated competitive or superior performance per dollar compared to NVIDIA’s GPUs in agentic inference workloads, according to benchmarks released by SemiAnalysis. The results cover four…
1 sourceSemiAnalysis -
Nvidia open-sources Flora to label robot video 125x cheaper than GPT-6 Astra
Nvidia has open-sourced Flora, a data engine for robot video labeling, claiming it reduces costs to 72 cents per hour compared to $88.50 for GPT-6 Astra—a 125x saving based on assumed GPU rental at $10 per hour. Flora…
1 sourceThe Decoder -
OpenMobile-2 open-source smartphone agents score 59.6 on SPA-Bench
Researchers from Nanjing University, SenseTime, and other universities released OpenMobile-2, an open-source project that trains AI smartphone agents in a simulated environment with over 110 apps. The larger model,…
1 sourceThe Decoder -
Anthropic says self-copying AI could target cheap TV boxes within months
Anthropic’s Frontier Red Team linked 15 off‑brand Android TV boxes, each costing about $55, and ran the open Gemma 4 model with 26 billion parameters on them. The boxes together generated roughly 0.4 tokens per second,…
1 sourcenotebookcheck.net -
Open-source decision models Jeff-Qwen3.5-0.8B and Jeff-Gemma4-E2B run in ~30ms on local hardware
Jeff is a set of small, fast decision models fine-tuned from Qwen3.5 and Gemma 4, designed for zero-shot classification tasks. The 0.8B-parameter model runs in about 22ms on an RTX PRO 6000 and 28ms on an Apple M4 Max,…
1 source primary source HN 59github.com -
Pistis introduces 27B- and 9B-parameter multimodal models via new training framework
Researchers released the Pistis model family on arXiv, featuring two multimodal large language models built on Qwen3.6 and Qwen3.5. The 27B-parameter model uses Qwen3.6, while the 9B-parameter model is based on…
1 source primary sourcearXiv cs.AI
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As of 5 November 2026: Google TPUv7 outperforms NVIDIA GPUs in agentic inference benchmarks. Google’s TPUv7 chip has demonstrated competitive or superior performance per dollar compared to NVIDIA’s GPUs in agentic inference workloads, according to benchmarks released by SemiAnalysis.