NVIDIA just dropped a thermonuclear benchmark bomb—and Wall Street's algo-traders are already mispricing it.The GB200 NVL72 isn't an upgrade. It's an extinction-level event for legacy AI hardware, pai...

<p><p>NVIDIA just dropped a thermonuclear benchmark bomb—and Wall Street&#39;s algo-traders are already mispricing it.</p><p>The GB200 NVL72 isn&#39;t an upgrade. It&#39;s an extinction-level event for legacy AI hardware, pairing with OpenAI&#39;s GPT-OSS models to rewrite the rules of machine learning throughput.</p><p>72-node liquid-cooled beast mode</p><p>Forget incremental gains. This black slab of silicon delivers exponential leaps in training efficiency while drawing less power than a hedge fund&#39;s weekend cocaine budget.</p><p>Open-source arms race escalates</p><p>GPT-OSS models now chew through unstructured data like a Bloomberg terminal on margin calls—except with actual risk management. The combo creates perfect infrastructure for next-gen decentralized AI networks.</p><p>Will institutions finally wake up? Or keep pretending CUDA cores are &#39;just a fad&#39; while retail builds the future?</p></p><img width="600" height="315" src="https://image.blockchain.news:443/features/D8E08E86F8EDBDDCD68414CF49BDD8B1401B11A69515DFF98E6B2B03EE9CF9D7.jpg" alt="NVIDIA Boosts AI Performance with GB200 NVL72 and OpenAI gpt-oss Models"></p>

<p>NVIDIA, in collaboration with OpenAI, has announced significant advancements in AI performance, leveraging the power of the <a href="https://www.btcc.com/en-US/academy/financial-investment/nvidia-nvda-stock-price-prediction-202320252030-is-nvda-a-good-investment" title="Nvidia" rel="nofollow">Nvidia</a> GB200 NVL72 system. The recent launch of the OpenAI gpt-oss-20b and gpt-oss-120b models promises to deliver up to 1.5 million tokens per second (TPS), marking a substantial leap in AI processing capabilities, according to NVIDIA.</p>
<h2>Enhanced AI Capabilities</h2>
<p>The gpt-oss models, known for their text-reasoning capabilities, are built using the mixture of experts (MoE) architecture with SwigGLU activations. These models utilize RoPE for attention layers, supporting a 128k context length, and are optimized for NVIDIA&#39;s Blackwell architecture. They are released in FP4 precision, compatible with an 80 GB data center GPU, and optimized for NVIDIA&#39;s advanced hardware.</p>
<h2>Collaborative Developments</h2>
<p>NVIDIA&#39;s collaboration with OpenAI extends to various open-source frameworks, including Hugging Face Transformers and NVIDIA TensorRT-LLM, to enhance model performance and developer accessibility. The gpt-oss-120b model, in particular, required extensive training, amounting to over 2.1 million GPU hours.</p>
<h2>Technical Specifications</h2>
<p>The gpt-oss-20b and gpt-oss-120b models feature a range of specifications to cater to diverse AI needs. These include varying transformer block counts, total parameters, and expert configurations, designed to optimize inference performance on NVIDIA&#39;s platforms.</p>
<h2>Deployment Options</h2>
<p>NVIDIA offers multiple deployment options for developers, including the use of vLLM and TensorRT-LLM for server setup and performance optimization. The GB200 NVL72 system is designed to handle high throughput, accommodating up to 50,000 concurrent users efficiently.</p>
<h2>Future Prospects</h2>
<p>With the introduction of these advanced models, NVIDIA aims to support a broad spectrum of AI applications from cloud to edge. Their efforts to integrate gpt-oss models across various platforms highlight a commitment to enhancing AI infrastructure and developer experience.</p>
<p>For more details on the deployment and capabilities of these models, visit the NVIDIA blog.</p>
Image source: Shutterstock
<ul>
                                    <li>nvidia</li>
                                    <li>openai</li>
                                    <li>ai models</li>
                                    <li>gb200 nvl72</li>

                            </ul>

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NVIDIA’s GB200 NVL72 &amp; OpenAI’s GPT-OSS Models Unleash AI Performance Frenzy

NVIDIA剛剛投放了一顆熱核效能基準測試炸彈——華爾街的ALGO交易員已經對其定價不當。<GB200 NVL72>不是一次升級。這是對傳統AI硬體的滅絕級事件，派...

<p><p>NVIDIA剛剛投放了一顆熱核基準測試炸彈——華爾街的演算法交易員已經錯誤定價了它。</p><p>GB200 NVL72不是一次升級。這是對傳統AI硬體的滅絕級事件，與OpenAI的GPT-OSS模型配對，重新定義機器學習吞吐量的規則。</p><p>72節點液冷野獸模式</p><p>忘記漸進式收益。這塊黑色矽板在訓練效率上實現指數級躍升，同時耗電量比對沖基金的週末可卡因預算還低。</p><p>開源軍備競賽升級</p><p>GPT-OSS模型現在像彭博終端處理保證金通話一樣處理非結構化資料——只是具有實際的風險管理。這種組合為下一代去中心化AI網路創造了完美基礎。</p><p>機構最終會醒悟嗎？還是繼續假裝CUDA核心只是"一時的潮流"，而散戶正在構建未來？</p></p><img width="600" height="315" src="https://image.blockchain.news:443/features/D8E08E86F8EDBDDCD68414CF49BDD8B1401B11A69515DFF98E6B2B03EE9CF9D7.jpg" alt="NVIDIA透過GB200 NVL72和OpenAI gpt-oss模型提升AI效能"></p>

<p>NVIDIA與OpenAI合作，宣佈在AI效能方面取得重大進展，利用Nvidia GB200 NVL72系統的強大功能。最近推出的OpenAI gpt-oss-20b和gpt-oss-120b模型有望每秒處理多達150萬個代幣，根據NVIDIA的說法，這標誌著AI處理能力的實質性飛躍。</p>
<h2>增強的AI能力</h2>
<p>以文字推理能力著稱的gpt-oss模型，採用專家混合（MoE）架構和SwigGLU啟用。這些模型使用RoPE進行注意力層，支援128k上下文長度，並針對NVIDIA的Blackwell架構進行了最佳化。它們以FP4精度釋出，相容80 GB資料中心GPU，並針對NVIDIA的先進硬體進行了最佳化。</p>
<h2>協作發展</h2>
<p>NVIDIA與OpenAI的合作延伸到各種開源框架，包括Hugging Face Transformers和NVIDIA TensorRT-LLM，以提高模型效能和開發者可訪問性。特別是gpt-oss-120b模型，其訓練耗時超過210萬GPU小時。</p>
<h2>技術規格</h2>
<p>gpt-oss-20b和gpt-oss-120b模型具有多種規格，以滿足不同的AI需求。這些包括不同的Transformer塊數量、總引數和專家配置，旨在最佳化NVIDIA平臺上的推理效能。</p>
<h2>部署選項</h2>
<p>NVIDIA為開發者提供多種部署選項，包括使用vLLM和TensorRT-LLM進行伺服器設定和效能最佳化。GB200 NVL72系統旨在高效處理高吞吐量，可同時容納多達5萬個併發使用者。</p>
<h2>未來前景</h2>
<p>透過推出這些先進模型，NVIDIA旨在支援從雲端到邊緣的廣泛AI應用。他們致力於在各個平臺上整合gpt-oss模型，凸顯了增強AI基礎設施和開發者體驗的承諾。</p>
<p>欲瞭解這些模型的部署和功能的更多詳情，請訪問NVIDIA部落格。</p>
圖片來源：Shutterstock
<ul>
                                    <li>nvidia</li>
                                    <li>openai</li>
                                    <li>ai模型</li>
                                    <li>gb200 nvl72</li>

                            </ul>

NVIDIA 的 GB200 NVL72 和 OpenAI 的 GPT-OSS 模型釋放 AI 性能狂潮

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