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NVIDIA Releases Nemotron 3.5 Transcribe Open Speech LLM

NVIDIA has released Nemotron 3.5 Transcribe, an open-weights speech LLM that handles 40 languages and recordings up to one hour from a single model. The hybrid Mamba-Transformer MoE has roughly 34B total and 4.3B active parameters, with built-in speaker attribution, word timestamps and prompt-selected output styles. NVIDIA reports 4.71% mean WER on nine English Open ASR sets, the best open-weights score, though commercial APIs still lead. Weights ship in BF16, FP8, NVFP4 and GGUF under a commercial-use license, with NVFP4 fitting an RTX 5090.

Why it matters: Developers get a concrete open, commercially licensed speech model that combines transcription, diarization, timestamps and translation, with deployment details and benchmark context.

MarkTechPostOct 29, 2026Score 88
NVIDIANemotronspeech recognition
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Nvidia releases open Nemotron 3.5 Transcribe for transcription, translation, and speaker recognition

Nvidia has released Nemotron 3.5 Transcribe, an open speech recognition model that handles transcription, speaker recognition, and translation and accepts instructions as text prompts. Nvidia says it leads several benchmarks while using only one-sixth of the active parameters of its strongest open rival. The release also includes a dataset of more than 800,000 hours of speech and tools for fine-tuning.

Why it matters: It gives readers a concrete new open speech model release with combined capabilities, benchmark claims, and supporting data and fine-tuning tools.

The DecoderOct 28, 2026Score 86
Nvidiaspeech recognitionopen models
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NVIDIA RTX Spark Laptops Add Local AI Models, Agent Controls and Games

NVIDIA announced updates for RTX Spark Windows laptops, which combine a Blackwell RTX GPU and Grace CPU with up to 128GB of unified memory for local AI workloads. The updates include Nemotron 3.5 Transcribe, an open-weight speech model for transcription, speaker attribution and translation, plus day-zero support for Liquid AI's LFM3 model family. NVIDIA App is adding controls for allocating GPU resources between foreground apps and background agents, while RTX Remix 1.6 and new game support bring AI-assisted modding and DLSS/ray tracing to the platform.

Why it matters: It bundles concrete local-AI model releases and agent resource controls with shipping hardware, giving developers a clear signal about on-device AI capabilities.

NVIDIA BlogOct 28, 2026Score 86
NVIDIARTX Sparklocal AI
Models

Nvidia releases open transcription model for recorded audio

Nvidia has released a free speech-to-text model capable of transcribing up to 40 languages. The model works on recordings rather than live audio, positioning it for meeting and medical transcription use cases. It leaves real-time transcription to competitors such as ElevenLabs.

TechCrunch AIOct 28, 2026Score 74
Nvidiaspeech recognitionopen models
Products

Nvidia open-sources Flora for cheaper robot video labeling

Nvidia has open-sourced Flora, a data engine that labels robot video using three fine-tuned Qwen3.5 models. Nvidia reports it labels an hour of robot video for 72 cents versus $88 with GPT-6 Astra, while scoring slightly higher on quality and catching robot action errors more reliably, though it sometimes lags on descriptive accuracy. Nvidia frames Flora as part of its push to control the robotics value chain.

The DecoderOct 25, 2026Score 76
NvidiaRobotics dataOpen-source models
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NVIDIA Releases Nemotron 3.5 Bolt E4B, an Open Small Model for Local Agents

NVIDIA released Nemotron 3.5 Bolt E4B, an open small language model built by RL post-training of Google's Gemma 4 E4B without supervised fine-tuning. It has 8B total and 4B effective parameters with 64K context, targeting local voice assistants, game NPCs and robot interfaces on RTX, Jetson and Spark hardware. NVIDIA reports top scores on 15 of 21 benchmarks in its own harness, but Qwen3.5-4B leads on Tau2-Bench and long-context tests. Weights, data and training recipes are public, with the Q4_K

Why it matters: It gives developers a concrete open-weight option for running capable tool-calling agents locally on constrained hardware, with disclosed training methods and honest benchmark weaknesses.

MarkTechPostOct 24, 2026Score 83
NVIDIANemotronGemma
Industry

Kazakhstan expands AI compute push with Firebird GPU deals and telco deployments

Kazakhstan's AI ecosystem is shifting from planning to deployment across infrastructure, models and applications, according to NVIDIA. Firebird has secured a U.S. export license for 45,000 NVIDIA Grace Blackwell GPUs and is building a first phase with Kazakhtelecom at Data Center Valley, targeting commercial launch in the third quarter of 2027, with a planned second phase potentially reaching about 500 megawatts. Kazakhtelecom has already deployed 400 NVIDIA H200 and 480 NVIDIA B300 GPUs in Asta

NVIDIA BlogOct 23, 2026Score 70
AI data centersNVIDIAKazakhstan
Products

NVIDIA Minerva Brings AI-Driven Observability to AI Factories

NVIDIA launched Minerva, an AIOps platform that combines telemetry from GPUs, networking, storage, schedulers and workloads to provide end-to-end observability for AI factories. It uses supervised and unsupervised ML to build a dynamic knowledge graph, detect anomalies and predict failures across large GPU clusters. Minerva includes a native AI assistant and supports external agentic AI tools for natural-language investigation and remediation. Partners including IREN, IBM, Jio, Lambda and Tesla

NVIDIA BlogOct 22, 2026Score 72
NVIDIAAI infrastructure managementAIOps
Industry

European banks build proprietary AI on open weight models and NVIDIA infrastructure

At GTC Berlin, European financial services organizations detailed production AI systems built on open weight models and NVIDIA accelerated computing. Revolut is rebuilding its stack around a single foundation model, PRAGMA, running in production for an initial 80 million customers, while Starling Bank, Lloyds and SBS described sovereign and transaction-focused intelligence platforms. Other deployments include bunq's agentic assistant Finn, which the company says matches leading closed models at

NVIDIA BlogOct 22, 2026Score 78
NVIDIAEuropean bankingopen models
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NVIDIA Expands Cosmos Platform for World Model Training and Deployment

NVIDIA announced an expansion of its Cosmos platform for building world models used in physical AI systems, adding training tools, simulation checkpoints and Cosmos Data Factory blueprints. The release introduces multimodal multisensory data curation, support for adapting open models such as GR00T, Alpamayo, QWEN and Pi0.5, and updated Cosmos 3 NIM microservices. NVIDIA also described Cosmos 3 Nano variants for simulation-based policy testing and a Metropolis VSS 3.3 blueprint. The company cited

Why it matters: It gives AI developers a concrete, detailed look at new open tooling and deployment options for building physical AI world models.

NVIDIA BlogOct 22, 2026Score 81
NVIDIAworld modelsphysical AI
Industry

NVIDIA Details European Retail Deployments of Open Models and Physical AI

NVIDIA outlined how European retailers and brands are deploying its open models, inference software and digital twin tooling across commerce and logistics. Shopify post-trained NVIDIA Nemotron 3.5 Lightning for a Sidekick subagent, reporting better accuracy on an internal benchmark alongside 90% lower serving costs and 7x faster responses. Otto Group extended an NVIDIA Omniverse-based warehouse simulation effort to its largest fulfillment center in Germany, and L'Oréal is using NVIDIA ALCHEMI an

NVIDIA BlogOct 22, 2026Score 75
NVIDIAEurope retail AIopen-weight models
Research Editor selected

Perplexity and NVIDIA Researchers Introduce JOLT: Joint Teacher-Student RL for Post-Training

Perplexity and NVIDIA researchers propose JOLT (Joint On-policy Learning and Teaching), a post-training method where a single model is trained as both teacher and student, with the teacher receiving privileged information and also being optimized. JOLT+ adds the student's own outcome reward to the distillation signal. On MATH, JOLT matched GRPO accuracy while using 6.5x fewer processed training tokens according to the authors' fitted curves, and JOLT+ led GRPO across the five tested settings. Th

Why it matters: It offers a concrete post-training technique with claimed compute savings and benchmark comparisons that RL practitioners can evaluate.

MarkTechPostOct 22, 2026Score 83
PerplexityNVIDIAReinforcement Learning
Tutorial

NVIDIA Nsight Python Tutorial: Profiling GPU Kernels In-Process from Jupyter

MarkTechPost walks through NVIDIA's open-source nsight-python library, which attaches Nsight Compute to a running Python process so developers can annotate code regions and get hardware metrics back as a pandas DataFrame. The tutorial covers run-count and confidence intervals, cache and clock control, a fp32/fp16 matrix-size sweep with a derived TFLOP/s metric, and hardware counters for distinguishing compute-bound from memory-bound kernels. It also demonstrates the upcoming 1.1 features: an exp

MarkTechPostOct 22, 2026Score 68
NVIDIANsight PythonGPU performance profiling
Products Editor selected

NVIDIA Expands Local AI Lineup at GTC Berlin With RTX Spark, DGX Spark Clusters, DGX Station and Recursive Flint

At GTC Berlin, NVIDIA detailed its local AI hardware and software stack, including RTX Spark PCs for personal agents, DGX Spark systems that can now cluster up to eight units with 1TB of unified memory, and DGX Station for larger teams, with a Windows version planned for December. NVIDIA Sync gains cluster support and a Model Launcher, DGX Station adds enterprise management integrations, and NVIDIA Cloud Functions is coming in early access to DGX Station. The company also highlighted Recursive F

Why it matters: It gives developers and enterprise IT teams a concrete, detailed look at new local AI hardware, clustering, model support and inference optimizations from NVIDIA.

NVIDIA BlogOct 21, 2026Score 83
NVIDIAlocal AI hardwareDGX Spark
Industry

Google Cloud and NVIDIA announce GA of Vera Rubin A5X cloud instances

NVIDIA and Google Cloud announced general availability of A5X instances built on NVIDIA Vera Rubin NVL72, ConnectX-9 SuperNICs and Google's Virgo Network, with GA slated for next month and planned expansion to Europe. Google Cloud says it plans to scale the Vera Rubin-based infrastructure to as many as 960,000 Rubin GPUs across multiple sites. Ineffable Intelligence, the startup founded by AlphaGo creator David Silver, was the first customer to access A5X, using it for large-scale reinforcement

NVIDIA BlogOct 21, 2026Score 77
NVIDIAGoogle CloudVera Rubin
Industry

NVIDIA Cloud Partners Expand European AI Infrastructure and Agent Safety Stack

NVIDIA announced that its cloud partners across Europe, the Nordics, Africa and Central Asia are expanding regional compute capacity for training and inference of agentic and physical AI workloads. The company cited Nscale tests in which NVIDIA DSX MaxLPS enabled 37% more GPUs and nearly 50% higher aggregate inference throughput within the same power budget, plus partner deployments spanning Vera Rubin, Groq 3 LPX and Blackwell Ultra. NVIDIA also introduced the OpenShell Reference Architecture a

NVIDIA BlogOct 21, 2026Score 68
NVIDIAAI infrastructureAI agents
Products

NVIDIA cuDSS reaches general availability, bringing GPU-accelerated sparse solvers to simulation tools

NVIDIA announced general availability of cuDSS, a CUDA-X library that moves large sparse linear-system solving, a repeated bottleneck in engineering and scientific simulation, onto GPUs. The company says partners including Applied Materials, Cadence, Dassault Systèmes, Siemens and Synopsys are integrating it, with vendor-reported speedups such as up to 10x at Applied Materials and 8-10x at Dassault Systèmes. cuDSS supports C, C++, Python and Fortran interfaces and is designed to scale from works

NVIDIA BlogOct 21, 2026Score 78
NVIDIAGPU-accelerated simulationscientific computing
Products

NVIDIA Expands Confidential Computing with New Confidential Bare Metal Option

NVIDIA announced Confidential Bare Metal, a new deployment option within its Confidential Computing portfolio that lets frontier model builders run sensitive workloads on dedicated third-party infrastructure while retaining control of models and data. The offering adds platform security controls for data in transit, platform integrity measurement and hardware-level access restrictions, alongside existing Confidential Containers and Confidential Virtual Machines modes. Support now extends to Grac

NVIDIA BlogOct 21, 2026Score 75
NVIDIAconfidential computingAI infrastructure security