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Edge AI Daily Morning Brief (October 30): Intel Plunges 21%, Anthropic…Developments
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Oct 30
TMTPost · AGI
Edge AI Daily Morning Brief (October 30): Intel Plunges 21%, Anthropic…
Intel reported third-quarter 2026 revenue of $16.5 billion and earnings per share of 52 cents, beating expectations, but its fourth-quarter revenue guidance of $15 billion to $16 billion fell short of the market's expectation of about $17.1 billion, and its gross margin guidance dropped from 43% to 38%; its stock price plunged about 21% in after-hours trading on October 29. Anthropic filed for a Nasdaq IPO on October 26 (ticker ANT), with revenue of $16.286 billion in the first half of 2026, up about 1,300% year over year, and second-quarter operating profit of $974 million. The U.S. Department of Justice has opened inquiries into whether Nvidia's acquisition of Hugging Face for about $12.93 billion affects AI competition.
NVIDIA RTX SparkRelated discussion
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Oct 29
Analytics India Magazine
NVIDIA Releases Nemotron 3.5 Transcribe Open-Weight Speech Model, Supporting 40 Languages
On October 28, NVIDIA released Nemotron 3.5 Transcribe, an open-weight speech model that can transcribe audio in 40 languages, translate speech, and identify speakers, and developers can control the transcription format with natural language instructions without retraining. The model consists of a Transformer speech encoder, a speaker diarization model, and the Nemotron 3.5 Lightning language model, with approximately 4.3 billion activated parameters, and the released checkpoint is labeled 30B-A4B. NVIDIA says it achieves an average word error rate of 4.71% on nine public test sets of the English Open ASR Leaderboard and 4.62% on seven languages of the multilingual leaderboard, and calls it the best open-weight model on both leaderboards; the model is released in BF16, FP8, and NVFP4 formats as well as GGUF files, under the OpenMDW-1.1 license.
gihyo.jp
NVIDIA Releases Speech Transcription and Translation Model Nemotron 3.5 Transcribe
On October 28, 2026, NVIDIA released the speech transcription and translation model Nemotron 3.5 Transcribe, supporting 40 languages including Japanese and capable of transcribing recordings up to 1 hour long. The model is an open-weight 30B MoE architecture that activates approximately 4B parameters during inference, can specify via text instructions whether to retain filler words and how numbers are written, and supports speaker diarization for up to 8 people and bidirectional Japanese-English translation. The weights are released on Hugging Face as NVIDIA-Nemotron-3.5-Transcribe-30B-A4B under the OpenMDW-1.1 license, with BF16, FP8, and NVFP4 versions and NeMo Speech fine-tuning tools provided.
Testing CatalogSelected
NVIDIA Releases Nemotron 3.5 Transcribe Open-Weight Speech Model
NVIDIA has released Nemotron 3.5 Transcribe, an open-weight 30B MoE model with approximately 4B active parameters. The model supports transcription in 40 languages, speaker attribution, translation, contextual prompting, and audio understanding, and ranks first in VoiceArena's 14-system comparison of speaker diarization plus ASR.
Latent SpaceSelected
Google DeepMind releases Gemini 4 Carbon, topping Artificial…
Google DeepMind has released Gemini 4 Carbon, which ranks first on the Artificial Analysis Intelligence Index v5 with a score of 59 and leads in 4 of 9 evaluations including HLE-Diamond and TB-Science. The model focuses on cybersecurity and long-horizon tasks, claiming 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench, and is initially available only to trusted cybersecurity personnel through the Fairwind Program. In terms of specifications, it supports a 1M token context and 1M maximum output, with input covering text, images, video, and speech, and output in text; Artificial Analysis lists a standard price of $4/$20 per million input/output tokens, plus a 50% launch discount.
MarkTechPost
NVIDIA Releases Nemotron 3.5 Transcribe: An Open-Source 30B MoE Speech Model…
NVIDIA has released Nemotron 3.5 Transcribe, an open-weight large speech model that supports 40 languages and up to 1 hour of audio per pass, and can select output formats such as verbatim, written, speaker-labeled, contextual, and translation via text instructions. The model has approximately 34B total parameters and about 4.3B activated parameters, adopts a hybrid Mamba-Transformer MoE architecture, can run in BF16 on a single H100 80GB, and the NVFP4 version at about 21GB can run on an RTX 5090. NVIDIA self-reports an average WER of 4.71% across 9 public English Open ASR test sets, the best result among open-weight models, though commercial APIs still lead; its shortcomings are that it only supports offline operation, and the Chinese far-field meeting cpCER is 34.95%.
Oct 28
Artificial Analysis
NVIDIA releases the Nemotron 3.5 Transcribe speech transcription model, tying for first among open-source models with 2.8% WER
NVIDIA has released the open-weight speech transcription model Nemotron 3.5 Transcribe, with 30B total parameters and 4B activated parameters. On Artificial Analysis's non-streaming speech transcription leaderboard, it achieves a 2.8% AA-WER, tying for first among open-source models with Mistral's Voxtral Small. On the speech agent dialogue dataset AA-AgentTalk, it leads Voxtral Small's 2.3% with 1.8%. Its activated parameters are 4B, while Voxtral Small's are 24B; other open-source models of comparable scale have a WER of about 4%.
NVIDIA BlogFirst-party
NVIDIA RTX Spark Laptop Update: Adds Nemotron 3.5 Transcribe and Local Agent Tools
NVIDIA announced multiple updates for RTX Spark thin-and-light laptops, including the open-weight voice model Nemotron 3.5 Transcribe, support for Liquid AI's LFM3 model family, and a control in the NVIDIA App that can allocate GPU resources between foreground applications and background agents. Nemotron 3.5 Transcribe supports transcription, speaker labeling, and translation in 40 languages, has approximately 4.3 billion active parameters, and is now available on Hugging Face. RTX Spark laptops are now shipping from ASUS, Dell, HP, Lenovo, Microsoft, and MSI, with a starting price of $2,599.
The New Stack
Nvidia Releases Nemotron 3.5 Transcribe Promptable Transcription Model
Nvidia has released the open-weight multilingual transcription model Nemotron 3.5 Transcribe, which ranks first on the Hugging Face Open ASR English open-source model leaderboard with an average word error rate of 5.33%. The model uses a 30B MoE architecture with 4B activated parameters, supports transcription in 40 languages and translation between 31 languages and English, can label speakers and distinguish up to 8 voices, handles recordings up to 1 hour long, but does not support real-time streaming. Users can provide instructions such as context and terminology before transcription; the model can be deployed with vLLM or run locally on a single GPU via NeMo-Speech.cpp; Nvidia has also released the data curation pipeline Granary v2 and a public manifest of approximately 463,062 hours across 48 languages.
TechCrunch AI
Nvidia Releases Open Source Transcription Model Nemotron 3.5 Transcribe
Nvidia has released the free open-weight model Nemotron 3.5 Transcribe, which can transcribe audio in up to 40 languages, and simultaneously launched version 2 of the open speech dataset Granary. The model supports translation between 31 languages and English, processes recordings up to one hour long, and distinguishes up to 8 speakers; Nvidia claims it outperforms competing products on benchmarks such as the Hugging Face Open ASR Leaderboard. The model has 30 billion parameters and can run on Jetson AGX Thor, DGX Spark, and Blackwell data center chips, but it only supports recorded audio and does not support live streams.
Hugging FaceFirst-partySelected
NVIDIA Releases Nemotron 3.5 Transcribe and Granary v2 Data Pipeline
NVIDIA has released the open-weight model Nemotron 3.5 Transcribe on Hugging Face and ModelScope, integrating transcription, speaker diarization, translation, and audio question answering into a single checkpoint. It supports transcription in 40 languages, translation between 31 languages and English, and speaker labeling in 13 languages, can process recordings up to 1 hour long, and can label up to 8 speakers. The model ranks first among open-weight models on the English leaderboard of the Hugging Face Open ASR Leaderboard with an average WER of 5.33%, and achieves 2.8% AA-WER on Artificial Analysis with approximately 4B activated parameters. The simultaneously released Granary v2 covers 48 languages and 463,062 hours of speech data, and the accompanying NeMo Speech fine-tuning recipe reduced WER on held-out speakers from 22.44% to 12.17% in a medical case.
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