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Saturday

  1. Artificial Analysis

    Artificial Analysis measured Meta Muse Spark Open inference throughput

    Artificial Analysis published preliminary test results on AA-AgentPerf for Meta's new open-weight model Muse Spark Open, an 816B-parameter, 42B-active MoE that scores 39 on the Artificial Analysis Intelligence Index. Tests show NVIDIA B300 and GB300 each reach about 150M tokens/s per megawatt under throughput-first configurations, with GB300 at about 108M and B300 at about 92M at 100 tok/s output speed; AMD MI355X reaches 70M tokens/s per megawatt at 65 tok/s. 46 of the model's 62 layers use 2,048-token sliding window attention, reducing KV cache requirements at 1M context by about 75% versus full attention; Meta released an NVFP4 checkpoint and AMD released an MXFP4 checkpoint.

    esults on AA-AgentPerf for Meta's new open-weight model Muse Spark Open, an 816B-parameter, 42B-active MoE that scores 39 on the Artificial Analysis Intelligence Index. Tests show NVIDIA B300 and GB300 each reach about 150M tokens/s per megawatt under throughput-first configurations, with GB300 at about 108M and B300 at about 92M at 100 tok/s output speed; AMD MI355X reaches 70M tokens/s per megawatt at 65 tok/s. 46 of the model's 62 layers use 2,048-token sliding window attention, reducing KV c

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  2. SiliconANGLE

    Managed services support keeps neocloud GPU compute healthy—SiliconANGLE

    Alpha Compute executive Tom Richer said at the Dell Technologies New York Symposium that small neoclouds find it difficult to build a complete GPU deployment team on their own, and Dell's managed services support is key to keeping clusters healthy and profitable after they go live. Alpha Compute provides sovereign and confidential computing with Dell and Intel hardware; its 72-node St. Louis cluster uses Dell's Nvidia Blackwell systems, InfiniBand networking and direct liquid cooling, and it has signed a $31.9 million non-recourse loan agreement secured by Nvidia B300 hardware.

    that small neoclouds find it difficult to build a complete GPU deployment team on their own, and Dell's managed services support is key to keeping clusters healthy and profitable after they go live. Alpha Compute provides sovereign and confidential computing with Dell and Intel hardware; its 72-node St. Louis cluster uses Dell's Nvidia Blackwell systems, InfiniBand networking and direct liquid cooling, and it has signed a $31.9 million non-recourse loan agreement secured by Nvidia B300 hardware.

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  3. SemiAnalysis

    SemiAnalysis benchmarks Trainium3's PyTorch training and Neuron Explorer profiler

    The SemiAnalysis engineering team benchmarked the native PyTorch training stack TorchNeuron and TorchTitan on Trainium3, training Qwen3-32B on 16 Trainium2 chips; eager mode reached 11,099 tokens/s and 23.89% MFU, while compiled mode reached 14,156 tokens/s and 30.47% MFU. The author considers the Neuron Explorer profiler superior to Nvidia's and AMD's solutions, but first-time compilation takes too long: the first-step compilation for the gpt-oss training recipe took 27 minutes 17 seconds. FlexAttention tests passed 89 of 96 cases, with all 7 failures due to compilation timeouts rather than numerical errors.

    um3, training Qwen3-32B on 16 Trainium2 chips; eager mode reached 11,099 tokens/s and 23.89% MFU, while compiled mode reached 14,156 tokens/s and 30.47% MFU. The author considers the Neuron Explorer profiler superior to Nvidia's and AMD's solutions, but first-time compilation takes too long: the first-step compilation for the gpt-oss training recipe took 27 minutes 17 seconds. FlexAttention tests passed 89 of 96 cases, with all 7 failures due to compilation timeouts rather than numerical errors.

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Thursday

  1. heise online

    Efficiency test: How much performance does the RTX Pro 6000 lose after lowering TDP

    heise conducts an efficiency test on the Nvidia RTX Pro 6000 Blackwell, measuring its performance loss at three power levels of 450 watts, 300 watts and 156 watts; the card has 96 GByte VRAM and targets AI and workstation scenarios. The test uses 450 watts as a reference corresponding to the previous-generation GeForce RTX 4090, 300 watts to the long-term limit of earlier flagship cards, and 156 watts to mid-to-low-end cards such as the GeForce RTX 5060 or Radeon RX 9060 XT. The full test data is available only to heise-Plus subscribers.

    heise conducts an efficiency test on the Nvidia RTX Pro 6000 Blackwell, measuring its performance loss at three power levels of 450 watts, 300 watts and 156 watts; the card has 96 GByte VRAM and targets AI and workstation scenarios. The test uses 450 watts as a reference corresponding to the previous-generation GeForce RTX 4090, 300 watts to the long-term limit of earlier flagship cards, and 156 watts to mid-to-low-end cards such as the GeForce RTX 5060 or Radeon RX 9060 XT. The full test data i

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  2. Rohan Paul

    Jensen Huang on neocloud financing and high cost of capital

    Jensen Huang said that Nvidia invests in neoclouds because they are good investments, which is different from an endorsement. Neoclouds have ample customers and are sold out; the only problem is a lack of working capital to buy land, power, buildings, and chips to fulfill commitments. He believes that rising borrowing costs are a side effect of enormous AI demand, not a flaw in the business model, and that when demand is high, other problems will be resolved.

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  3. xAI News

    xAI launches the SpaceX Super Intelligence partner network to build enterprise products on Grok

    xAI launches the SpaceX Super Intelligence partner network for companies building products, solutions, and services on Grok, divided into two categories: Transformation Partners and Marketplace Partners. More than 130 companies have already participated in the program's early access phase, and the Forward Deployed Engineer certification program has trained engineers at more than 30 organizations. Bain & Company, Databricks, NVIDIA, Snowflake, and others are among the first Launch Partners.

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  4. Tech.eu

    RhymeQ Emerges from Stealth with $2.2M to Simplify Quantum Programming

    Quantum computing startup RhymeQ has emerged from stealth, closing a $2.2 million pre-seed funding round led by Ground State Ventures, with participation from Vanagon Ventures, Plug and Play, and Freiraum Ventures. Its platform Rhyme provides an abstraction layer that lets developers with basic Python skills write and debug code for quantum computers; the compiler translates the code for quantum hardware and supports multiple quantum processors. RhymeQ is an NVIDIA Inception member, and its technology is compatible with NVIDIA's CUDA-Q platform.

    tealth, closing a $2.2 million pre-seed funding round led by Ground State Ventures, with participation from Vanagon Ventures, Plug and Play, and Freiraum Ventures. Its platform Rhyme provides an abstraction layer that lets developers with basic Python skills write and debug code for quantum computers; the compiler translates the code for quantum hardware and supports multiple quantum processors. RhymeQ is an NVIDIA Inception member, and its technology is compatible with NVIDIA's CUDA-Q platform.

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  5. UCSD Hao AI Lab

    FastVideo FastH3 Omni Runs Locally on DGX Spark, RTX GPUs, and Apple MLX

    Hao AI Lab announced that FastVideo FastH3 Omni can run locally on NVIDIA DGX Spark, RTX GPUs, and Apple MLX. Generating a 5-second 480p video from a single photo and a prompt takes about 3 minutes, or about 2 minutes on two Sparks; FastH3 T2AV takes 52.6 seconds on a single Spark and 30.7 seconds on two Sparks. The clips in the demo video were all generated by DGX Spark using an 8-step NVFP4 checkpoint, and blog, Cookbook, and Hugging Face links are provided.

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Friday

  1. CTech

    The next batch of big AI winners will build the infrastructure that giants depend on

    Doron Zauer, partner at Earth & Beyond Ventures, believes that competition at the AI application layer is intense and easily commoditized, while physical infrastructure such as silicon architecture, advanced materials, and connectivity technologies are long-term advantages that are hard to replicate. Israel has deep accumulated strength in chip design, photonics, and high-speed communications, and entrepreneurs can target the architectural bottlenecks encountered by giants such as Nvidia, Apple, Intel, and Google. Commercialization success depends on yield, reliability, and system integration, and early validation with industrial buyers and design partners is crucial.

    silicon architecture, advanced materials, and connectivity technologies are long-term advantages that are hard to replicate. Israel has deep accumulated strength in chip design, photonics, and high-speed communications, and entrepreneurs can target the architectural bottlenecks encountered by giants such as Nvidia, Apple, Intel, and Google. Commercialization success depends on yield, reliability, and system integration, and early validation with industrial buyers and design partners is crucial.

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  2. Testing Catalog

    October 23 AI Daily: MiniMax open-sources M3.1 Flash, OpenAI launches Decisions API

    MiniMax open-sources M3.1 Flash, a 428B-parameter MoE with 23B activated parameters, gaining day-one support from Together, SGLang, vLLM and NVIDIA NeMo. OpenAI's Decisions API is officially available, powered by GPT-6 Luna, with classification and decision speed improved by up to 10x, at an input price of $0.10 per million tokens. Anthropic's Claude models are officially available on Google Cloud, and starting next week, Claude sessions on Pro, Max and Team plans will run in auto mode by default.

    MiniMax open-sources M3.1 Flash, a 428B-parameter MoE with 23B activated parameters, gaining day-one support from Together, SGLang, vLLM and NVIDIA NeMo. OpenAI's Decisions API is officially available, powered by GPT-6 Luna, with classification and decision speed improved by up to 10x, at an input price of $0.10 per million tokens. Anthropic's Claude models are officially available on Google Cloud, and starting next week, Claude sessions on Pro, Max and Team plans will run in auto mode by defaul

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  3. Semiconductor Industry Observer

    MSI releases EdgeMesa N AI+ mini PC, 1.3L chassis runs 120B large model locally

    MSI has released the EdgeMesa N AI+ mini PC, with a volume of 1.3 liters, equipped with the NVIDIA RTX Spark N1X superchip and up to 128GB of LPDDR5X unified memory, with running 120B-parameter large models locally as its primary design goal. The chip integrates a 20-core Grace CPU and a Blackwell GPU with 6144 CUDA cores; the unified memory pool lets model weights and KV cache share the same physical memory. Referring to measured results from the DGX Spark on the same platform, generation speed for 120B-class models is about 15 to 59 tokens/s, limited by 273GB/s memory bandwidth; official pricing has not yet been announced, and the article estimates it may fall in the 30,000 to 40,000 RMB range.

    MSI has released the EdgeMesa N AI+ mini PC, with a volume of 1.3 liters, equipped with the NVIDIA RTX Spark N1X superchip and up to 128GB of LPDDR5X unified memory, with running 120B-parameter large models locally as its primary design goal. The chip integrates a 20-core Grace CPU and a Blackwell GPU with 6144 CUDA cores; the unified memory pool lets model weights and KV cache share the same physical memory. Referring to measured results from the DGX Spark on the same platform, generation speed

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  4. English text is being prepared.

    Procore deepens cooperation with NVIDIA, using Omniverse digital twins to simulate building construction scenarios

    At Groundbreak 2026, construction management software company Procore Technologies announced a deepened collaboration with NVIDIA to bring digital twin and simulation capabilities based on NVIDIA Omniverse into complex construction projects; the feature is currently in closed beta. Users can switch between Procore's Model Manager and Realism Mode to simulate in a high-fidelity 3D environment how real-world conditions such as extreme weather affect construction; the collaboration is mainly aimed at large infrastructure projects such as AI data centers.

    At Groundbreak 2026, construction management software company Procore Technologies announced a deepened collaboration with NVIDIA to bring digital twin and simulation capabilities based on NVIDIA Omniverse into complex construction projects; the feature is currently in closed beta. Users can switch between Procore's Model Manager and Realism Mode to simulate in a high-fidelity 3D environment how real-world conditions such as extreme weather affect construction; the collaboration is mainly aimed

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  5. The Paper

    MiniMax open-sources the M3.1 Flash model, reducing usage cost by 70%

    MiniMax announced on October 23 the open-sourcing of the M3.1 Flash model, which processed over 100 trillion tokens within 72 hours of launch. Compared with the previous generation M3, M3.1 Flash has comprehensively improved capabilities, with usage cost reduced by 70% and online inference speed increased by nearly 3 times. MiniMax stated it will work with chip manufacturers such as Huawei Ascend, NVIDIA, and AMD, as well as inference frameworks and communities such as vLLM, SGLang, and Hugging Face, to advance day-one open-source integration.

    of the M3.1 Flash model, which processed over 100 trillion tokens within 72 hours of launch. Compared with the previous generation M3, M3.1 Flash has comprehensively improved capabilities, with usage cost reduced by 70% and online inference speed increased by nearly 3 times. MiniMax stated it will work with chip manufacturers such as Huawei Ascend, NVIDIA, and AMD, as well as inference frameworks and communities such as vLLM, SGLang, and Hugging Face, to advance day-one open-source integration.

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  6. Fireworks AI

    Fireworks AI Media Coverage Roundup

    Fireworks AI's media coverage roundup page lists several items: its CEO Lin Qiao said on a podcast that the company processes 40 trillion tokens per day, and claimed this scale exceeds OpenAI; another report said this Nvidia-backed company reached a valuation of $17.5B. The page also includes discussions on AI costs, agent control issues, and the difference between training and inference.

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  7. Leitech

    Mifeng jointly launches the embodied evaluation platform RoboColiseum, with GPT-6, Opus 5.5, and Gemini 4 competing head-to-head

    Mifeng Technology, together with nearly 20 institutions including Hugging Face, NVIDIA, and Tsinghua University, jointly launched the embodied evaluation platform RoboColiseum, and announced this round's results on October 20: Claude Opus 5.5 ranked first overall among the four flagship models, followed closely by GPT-6 Astra. GPT-6 Astra scored 99.35 on instruction following, while Opus 5.5 performed better on spatial understanding and general manipulation and consumed the fewest tokens. The platform contains 78 simulated evaluation tasks, with a simulation-to-real-world correlation of 89.5%, and since launching in August, more than 100 teams have participated.

    Mifeng Technology, together with nearly 20 institutions including Hugging Face, NVIDIA, and Tsinghua University, jointly launched the embodied evaluation platform RoboColiseum, and announced this round's results on October 20: Claude Opus 5.5 ranked first overall among the four flagship models, followed closely by GPT-6 Astra. GPT-6 Astra scored 99.35 on instruction following, while Opus 5.5 performed better on spatial understanding and general manipulation and consumed the fewest tokens. The pl

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  8. MiniMax

    MiniMax M3.1 Flash Gets Day-One Support from SGLang and Miles

    MiniMax announced that M3.1 Flash is ready from inference to RL, with SGLang and Miles providing support on the very first day of release. According to SGLang, the model achieves over 1K tok/s for bs1 decode on SGLang, supports NVIDIA Blackwell and Hopper (GB300/B300/B200/H200) as well as AMD Instinct MI350X and MI355X, and supports MiniMax's DSpark draft model along with HiCache and multimodal input.

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  9. The Elec

    KT Cloud Breaks Ground on 50MW AI Data Center in Ansan

    On October 22, KT Cloud broke ground on its own 50MW AI data center in Ansan, Gyeonggi Province. The facility has a total floor area of approximately 36,878 square meters, with 9 floors above ground and 2 below, and is scheduled for completion in 2029. All server rooms in the facility will support liquid cooling, and it will use a high-load structural design to accommodate Nvidia's next-generation Vera Rubin GPUs, while also introducing a free-cooling system to reduce cooling energy consumption. The project is part of its long-term strategy to secure 1GW of AI data center capacity by 2031.

    The facility has a total floor area of approximately 36,878 square meters, with 9 floors above ground and 2 below, and is scheduled for completion in 2029. All server rooms in the facility will support liquid cooling, and it will use a high-load structural design to accommodate Nvidia's next-generation Vera Rubin GPUs, while also introducing a free-cooling system to reduce cooling energy consumption. The project is part of its long-term strategy to secure 1GW of AI data center capacity by 2031.

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  10. The Next Platform

    How Mixx Technologies Paves the Way for All-Optical Scale-up Networks

    Photonics startup Mixx Technologies is betting on all-optical scale-up networks. Its first product, the SxC connector, can accommodate 64 fibers within a single connector, and the company claims it can arrange 1,000 fibers within 800mm2. The company has laid out a three-step roadmap of NPO optical engines, CPO, and optical circuit switches. Its first NPO module is targeted for launch in 2028 or 2029, and CPO products are expected to be released by the end of this decade. If Nvidia's Vera Rubin NVL576 is estimated at one pair of fibers per SerDes, it would require approximately 20,736 pairs of fiber connections to connect 8 NVL72 racks.

    s within a single connector, and the company claims it can arrange 1,000 fibers within 800mm2. The company has laid out a three-step roadmap of NPO optical engines, CPO, and optical circuit switches. Its first NPO module is targeted for launch in 2028 or 2029, and CPO products are expected to be released by the end of this decade. If Nvidia's Vera Rubin NVL576 is estimated at one pair of fibers per SerDes, it would require approximately 20,736 pairs of fiber connections to connect 8 NVL72 racks.

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  11. Cohere Product and Research Blog

    Cohere Model Vault Launches Confidential Computing Public Beta

    Cohere announced that the confidential computing feature of Model Vault has entered public beta, providing hardware-level isolation for hosted model inference based on the NVIDIA H100 GPU confidential computing capability on Microsoft Azure. This feature extends the scope of encryption from data at rest and in transit to prompts, documents, responses, and model execution during inference; after end-to-end encryption on the application workload side, decryption can only occur in a confidential environment that has passed remote attestation. Customers can cryptographically verify the hardware, firmware, and software configuration before sending sensitive data; if it does not comply with the security policy, the client will refuse to send the request. The existing Model Vault API and request format remain unchanged.

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    Cohere announced that the confidential computing feature of Model Vault has entered public beta, providing hardware-level isolation for hosted model inference based on the NVIDIA H100 GPU confidential computing capability on Microsoft Azure. This feature extends the scope of encryption from data at rest and in transit to prompts, documents, responses, and model execution during inference; after end-to-end encryption on the application workload side, decryption can only occur in a confidential en

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  12. Cohere Product and Research Blog

    Cohere Model Vault Launches Verifiable Confidential AI Inference

    Cohere has launched confidential computing capabilities on Model Vault, currently in public beta, running on NVIDIA GPUs on Microsoft Azure. The feature combines confidential CPU and GPU execution, OHTTP end-to-end encryption of request content, and remote attestation, allowing customers to verify the target environment before releasing sensitive data. Cohere plans to open-source the confidential inference stack and advance support for NVIDIA Blackwell and B200 GPUs.

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