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nemotron-3.5-asr-streaming-0.6b

NVIDIAhuggingface.co/nvidia/nemotron-3.5-asr-streaming

Open in Graph
data quality53

Updated 10 h ago · first seen 11 Sept 2026

model_01M294ZPG8HB05BERG3MQ5TMVT

Overview

Identity

Identity block not returned by the API for this entity.

Openness

Openness not classified yet — no sourced evidence to place this model in the ontology.

Key facts

Release date

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Architecture

Architecture

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Model type

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Parameters

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium

Weights dtype

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

File size

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Library name

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Pipeline tag

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium

Hugging Face repo

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium

Capabilities

Modalities

Modalities unavailable.

Capabilities

  • Tool calling

    Unavailable

  • Structured output

    Unavailable

  • Reasoning

    Unavailable

  • Vision

    Unavailable

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

No capability flags have been observed from a source yet — we do not infer them.

Languages

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Hardware fit37

Estimated

37 of 37 device × quantization combinations fit.

Run locally: your machine →
Estimated hardware fit
HardwareQuantizationDevice memoryEst. memoryFits
Apple M3 Ultra4bit0.9 GB est.Yes
Mac Studio (Apple M5 Ultra)4bit0.9 GB est.Yes
Apple M2 Ultra4bit0.9 GB est.Yes
Apple M1 Ultra4bit0.9 GB est.Yes
Apple M3 Max4bit0.9 GB est.Yes
Apple M4 Max4bit0.9 GB est.Yes
Mac Studio (Apple M5 Max)4bit0.9 GB est.Yes
MacBook Pro (Apple M5 Max)4bit0.9 GB est.Yes
Apple M2 Max4bit0.9 GB est.Yes
Apple M1 Max4bit0.9 GB est.Yes
Apple M4 Pro4bit0.9 GB est.Yes
Mac mini (Apple M5 Pro)4bit0.9 GB est.Yes
MacBook Pro (Apple M5 Pro)4bit0.9 GB est.Yes
Apple M3 Pro4bit0.9 GB est.Yes
Apple M1 Pro4bit0.9 GB est.Yes
Apple M2 Pro4bit0.9 GB est.Yes
Apple M44bit0.9 GB est.Yes
iMac (Apple M4)4bit0.9 GB est.Yes
Mac mini (Apple M6)4bit0.9 GB est.Yes
MacBook Air (Apple M5)4bit0.9 GB est.Yes
MacBook Pro (Apple M5)4bit0.9 GB est.Yes
Apple M24bit0.9 GB est.Yes
Apple M34bit0.9 GB est.Yes
Apple M14bit0.9 GB est.Yes
NVIDIA GeForce RTX 30904bit24 GB0.9 GB est.Yes
NVIDIA GeForce RTX 40904bit24 GB0.9 GB est.Yes
NVIDIA GeForce RTX 50904bit32 GB0.9 GB est.Yes
NVIDIA A100 80GB4bit80 GB0.9 GB est.Yes
NVIDIA H100 SXM4bit80 GB0.9 GB est.Yes
NVIDIA H100 NVL4bit94 GB0.9 GB est.Yes
NVIDIA DGX Spark4bit128 GB0.9 GB est.Yes
NVIDIA H2004bit141 GB0.9 GB est.Yes
NVIDIA H200 NVL4bit141 GB0.9 GB est.Yes
NVIDIA B2004bit180 GB0.9 GB est.Yes
AMD Instinct MI300X4bit192 GB0.9 GB est.Yes
AMD Instinct MI325X4bit256 GB0.9 GB est.Yes
NVIDIA DGX B2004bit1,440 GB0.9 GB est.Yes
Assumptions (6)
  • Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead.
  • bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
  • KV cache approximated at 0.5 GB per 8 192 tokens of context, independent of architecture (GQA/MLA models need less).
  • A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
  • Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
  • Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).

Papers2

Datasets6

Change history25

Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.

Viewing AI Atlas as of 12 Sept 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.

Back to today →

Attributes as of 12 Sept 2026 26 claims in force

Release date
15 May 2026
Openness
open-weights
License
Other
Architecture
Nemotron3_5AsrForRNNT
Parameters
638M
Languages
en, es, de, fr, it, ar, ja, ko, pt, ru, hi, zh, vi, he, nl, cs, da, pl, no, sv, th, tr, bg, el, et, fi, hr, hu, lt, lv, ro, sk, uk, mt, sl
Quantization format
gguf
File size
2.5 GB
Hugging Face repo
nvidia/nemotron-3.5-asr-streaming-0.6b
Pipeline tag
automatic-speech-recognition
Downloads
722,175
Likes
1,102
Datasets
nvidia/Granary, multilingual_librispeech, fleurs, mozilla-foundation/common_voice_8_0, voxpopuli, europarl
Gated
No
Hf inference providers
deepinfra, fal-ai, together
Is quantized
Yes
Last modified
2026-09-10T16:49:07+00:00
Library name
nemo
License name
openmdw-1.1
License url
https://openmdw.ai/license/1-1/
Downloads all time
2,393,449
Model type
nemotron3_5_asr
Tags
nemo, safetensors, gguf, nemotron3_5_asr, feature-extraction, transformers, speech-recognition, cache-aware ASR, automatic-speech-recognition, streaming-asr, multilingual, speech, audio, FastConformer, RNNT, Parakeet, ASR, pytorch, NeMo, en, es, de, fr, it, ar, ja, ko, pt, ru, hi
Weights available
Yes
Weights dtype
F32
25 claims · 25 properties

Release daterelease_date1

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ValueValid from → toStatusSourceConfidenceExtractor
15 May 2026currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Opennessopenness1

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open-weightscurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Licenselicense1

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ValueValid from → toStatusSourceConfidenceExtractor
othercurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Architecturearchitecture1

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ValueValid from → toStatusSourceConfidenceExtractor
Nemotron3_5AsrForRNNTcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Parametersparameter_count1

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ValueValid from → toStatusSourceConfidenceExtractor
638McurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Languageslanguages1

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ValueValid from → toStatusSourceConfidenceExtractor
en, es, de, fr, it, ar, ja, ko, pt, ru, hi, zh, vi, he, nl, cs, da, pl, no, sv, th, tr, bg, el, et, fi, hr, hu, lt, lv, ro, sk, uk, mt, slcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Quantization formatquant_format1

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ValueValid from → toStatusSourceConfidenceExtractor
ggufcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

File sizefile_size_gb1

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2.5 GBcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Hugging Face repohf_repo1

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nvidia/nemotron-3.5-asr-streaming-0.6bcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Pipeline tagpipeline_tag1

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ValueValid from → toStatusSourceConfidenceExtractor
automatic-speech-recognitioncurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Model cardmodel_card_url1

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https://huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6bcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Downloadsmetric.downloads1

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ValueValid from → toStatusSourceConfidenceExtractor
722,175currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Likesmetric.likes1

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ValueValid from → toStatusSourceConfidenceExtractor
1,102currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Datasetsdatasets1

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ValueValid from → toStatusSourceConfidenceExtractor
nvidia/Granary, multilingual_librispeech, fleurs, mozilla-foundation/common_voice_8_0, voxpopuli, europarlcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Gatedgated1

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ValueValid from → toStatusSourceConfidenceExtractor
NocurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Hf inference providershf_inference_providers1

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ValueValid from → toStatusSourceConfidenceExtractor
deepinfra, fal-ai, togethercurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Is quantizedis_quantized1

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YescurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Last modifiedlast_modified1

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ValueValid from → toStatusSourceConfidenceExtractor
2026-09-10T16:49:07+00:00currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Library namelibrary_name1

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nemocurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

License namelicense_name1

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ValueValid from → toStatusSourceConfidenceExtractor
openmdw-1.1currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

License urllicense_url1

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ValueValid from → toStatusSourceConfidenceExtractor
https://openmdw.ai/license/1-1/currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Downloads all timemetric.downloads_all_time1

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ValueValid from → toStatusSourceConfidenceExtractor
2,393,449currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Model typemodel_type1

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nemotron3_5_asrcurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Tagstags1

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nemo, safetensors, gguf, nemotron3_5_asr, feature-extraction, transformers, speech-recognition, cache-aware ASR, automatic-speech-recognition, streaming-asr, multilingual, speech, audio, FastConformer, RNNT, Parakeet, ASR, pytorch, NeMo, en, es, de, fr, it, ar, ja, ko, pt, ru, hicurrentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Weights dtypeweights_dtype1

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ValueValid from → toStatusSourceConfidenceExtractor
F32currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

Provenance

Attributed facts

25

Source tiers

T225

Freshest observation

10 h ago

Conflicts

None

Source documents 3

Source documents
SourceDocumentTypeTierLast observedSnapshots
Hugging Face Hub (public pages, model cards, papers)huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b model_pageT2· Quality secondary10 h ago3
Hugging Face Hub (public pages, model cards, papers)huggingface.co/models?author=nvidia&p=0&sort=downloads listingT2· Quality secondary10 h ago3
Hugging Face Hub (public pages, model cards, papers)huggingface.co/nvidia/nemotron-3.5-asr-streaming-0.6b/raw/main/README.md model_cardT2· Quality secondary11 h ago1

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

Data quality (53/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →