Nemotron-Personas-Finance-Japan synthetic dataset covers Japan
The Hugging Face post, under an NVIDIA path, gives no further details beyond the title.
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Stories tagged #nemotron
NVIDIA OpenShell secures Korean AI agent ecosystems
Hyundai Motor Group and LG AI Research partner with NVIDIA for secure agentic AI.
NVIDIA Highlights Chris Alexiuk as Top Fan of Open Nemotron Models
Senior product research engineer Chris Alexiuk promotes NVIDIA Nemotron open models for developers, emphasizing transparency and accessibility in AI.
Box to embed Nvidia Nemotron in content retrieval
Enterprise Advance customers get it early next year; Nvidia expects faster queries and 90% fewer tokens.
AutoCompress Framework for Hardware-Guided Model Compression
AutoCompress optimizes LLM architectures for latency and memory constraints, improving accuracy over Minitron by up to 6.57 percentage points.
NVIDIA publishes Hugging Face post titled nemotron-halloween
The listing gives only the title; no model, release, or product details are available.
Allen Telescope Array uses NVIDIA agents to scan SETI data in flight
DAQIRI streams terabits per second into GPU memory, and the pipeline has already detected a Crab Nebula pulsar in real time.
Samaya releases Sterling, a 3B-active finance research model
On Samaya’s own benchmark it scores 58.9% at $0.61 per question versus 55.9% and $6.89 for Claude Fable 5.1.
NVIDIA releases open Nemotron 3.5 Transcribe, a 30B MoE speech model
The open model transcribes 40 languages while activating about 4 billion of its 30 billion parameters.
Nvidia releases open Nemotron 3.5 Transcribe speech model
Nvidia says the 30-billion-parameter model keeps about 4 billion active and tops open-weight English ASR models.
NVIDIA RTX Spark laptops add Nemotron 3.5, agent controls and DLSS games
Nemotron 3.5 Transcribe is open-weight today on Hugging Face, with about 4.3 billion active parameters.
Nvidia releases open-weight Nemotron 3.5 Transcribe speech model
Nvidia also shipped Granary version 2 and says the model handles recorded audio only, not live streams.
Survival LLM runs an offline emergency assistant on a local PC
It picks among Nemotron, Qwen and Granite models by memory and cites FEMA, CDC and other local sources.
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NVIDIA releases open Nemotron 3.5 Bolt E4B 4GB
The headline positions the small open model for local voice agents, game characters and robots.
RSI Arena studies autonomous post-training of Nemotron with human feedback
The paper reports GPT-6 Astra closed a median 76% of the base-to-Instruct gap, and eight of ten models improved after a second stage.
Unsloth publishes GGUF of NVIDIA Nemotron 3.5 Bolt E4B
The Q4_K_M build has 8B total parameters, 4B effective, and a 64K-token context.
European public bodies adopt NVIDIA open models under local control
Work covers the Commission, Poland, the UK, Germany and France, including imaging, personas and a classified cloud plan.
European retailers deploy NVIDIA open models and digital twins
Shopify says a post-trained Nemotron model cut serving costs 90% and responded 7x faster on an internal test.
NVIDIA announces Nemotron 3.5 Embed, Rerank, and Parse models
The post body was unavailable, so sizes, benchmarks, licenses, and release status are not stated.
NVIDIA expands Agent Toolkit to ground enterprise agents in company data
The expansion adds Agent Knowledge Foundation, Kumo models, OpenShell, and NemoClaw, with adopters including Palantir, Databricks, and Snowflake.
NVIDIA announces open models for language, robotics, biology and quantum
The portfolio adds Nemotron 3.5, Kumo, Cosmos 3.5, Alpamayo 2 Edge, BioNeMo RFD4-Proteina and Ising.
Barcelona Supercomputing Center opens AI Factory access via NVIDIA
BSC says it has delivered more than 800 services since April 2025 and named three AI Champions.
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Nvidia releases open Nemotron 3.5 models for agents and PCs
The 120-billion-parameter Super VL and 74-billion-parameter Bolt model are available now; Bolt E4B follows later this month.
EBU and NVIDIA expand sovereign AI plan for European broadcasters
Adobe says GPU-backed Frame.io search is about 5x faster at embeddings, with up to 4x throughput and 5x lower latency.