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granite-embedding-311m-multilingual-r2

IBMhuggingface.co/ibm-granite/granite-embedding-311

Open in Graph
data quality53

Updated 10 h ago · first seen 11 Sept 2026

model_01M294YP7PFNFB6SMSRD5EJBG6

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 Ultra4bit—0.7 GB est.Yes
Mac Studio (Apple M5 Ultra)4bit—0.7 GB est.Yes
Apple M2 Ultra4bit—0.7 GB est.Yes
Apple M1 Ultra4bit—0.7 GB est.Yes
Apple M3 Max4bit—0.7 GB est.Yes
Apple M4 Max4bit—0.7 GB est.Yes
Mac Studio (Apple M5 Max)4bit—0.7 GB est.Yes
MacBook Pro (Apple M5 Max)4bit—0.7 GB est.Yes
Apple M2 Max4bit—0.7 GB est.Yes
Apple M1 Max4bit—0.7 GB est.Yes
Apple M4 Pro4bit—0.7 GB est.Yes
Mac mini (Apple M5 Pro)4bit—0.7 GB est.Yes
MacBook Pro (Apple M5 Pro)4bit—0.7 GB est.Yes
Apple M3 Pro4bit—0.7 GB est.Yes
Apple M1 Pro4bit—0.7 GB est.Yes
Apple M2 Pro4bit—0.7 GB est.Yes
Apple M44bit—0.7 GB est.Yes
iMac (Apple M4)4bit—0.7 GB est.Yes
Mac mini (Apple M6)4bit—0.7 GB est.Yes
MacBook Air (Apple M5)4bit—0.7 GB est.Yes
MacBook Pro (Apple M5)4bit—0.7 GB est.Yes
Apple M24bit—0.7 GB est.Yes
Apple M34bit—0.7 GB est.Yes
Apple M14bit—0.7 GB est.Yes
NVIDIA GeForce RTX 30904bit24 GB0.7 GB est.Yes
NVIDIA GeForce RTX 40904bit24 GB0.7 GB est.Yes
NVIDIA GeForce RTX 50904bit32 GB0.7 GB est.Yes
NVIDIA A100 80GB4bit80 GB0.7 GB est.Yes
NVIDIA H100 SXM4bit80 GB0.7 GB est.Yes
NVIDIA H100 NVL4bit94 GB0.7 GB est.Yes
NVIDIA DGX Spark4bit128 GB0.7 GB est.Yes
NVIDIA H2004bit141 GB0.7 GB est.Yes
NVIDIA H200 NVL4bit141 GB0.7 GB est.Yes
NVIDIA B2004bit180 GB0.7 GB est.Yes
AMD Instinct MI300X4bit192 GB0.7 GB est.Yes
AMD Instinct MI325X4bit256 GB0.7 GB est.Yes
NVIDIA DGX B2004bit1,440 GB0.7 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

Timeline1

Full timeline →

Change history22

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
20 Apr 2026
Openness
open-weights
License
Apache-2.0
Architecture
ModernBertModel
Parameters
311.7M
Languages
ar, az, bg, bn, ca, cs, da, de, el, en, es, et, fa, fi, fr, he, hi, hr, hu, id, is, it, ja, ka, kk, km, ko, lt, lv, mr, ms, nl, no, pl, pt, ro, ru, sk, sl, sq, sr, sv, sw, te, th, tl, tr, uk, ur, uz, vi, zh
Quantization format
onnx
File size
0.6 GB
Hugging Face repo
ibm-granite/granite-embedding-311m-multilingual-r2
Pipeline tag
feature-extraction
Downloads
120,372
Likes
130
Commercial use allowed
Yes
Derivatives allowed
Yes
Gated
No
Hf inference providers
hf-inference
Is quantized
Yes
Last modified
2026-05-18T20:15:41+00:00
Library name
sentence-transformers
Downloads all time
721,749
Model type
modernbert
Redistribution allowed
Yes
Tags
sentence-transformers, onnx, safetensors, openvino, modernbert, feature-extraction, granite, embeddings, transformers, multilingual, mteb, sentence-similarity, matryoshka, ar, az, bg, bn, ca, cs, da, de, el, en, es, et, fa, fi, fr, he, hi
Weights available
Yes
Weights dtype
BF16
22 claims · 22 properties

Release daterelease_date1

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

Opennessopenness1

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open-weights → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Licenselicense1

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apache-2.0 → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Architecturearchitecture1

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ModernBertModel → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Parametersparameter_count1

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ValueValid from → toStatusSourceConfidenceExtractor
311.7M → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Languageslanguages1

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ValueValid from → toStatusSourceConfidenceExtractor
ar, az, bg, bn, ca, cs, da, de, el, en, es, et, fa, fi, fr, he, hi, hr, hu, id, is, it, ja, ka, kk, km, ko, lt, lv, mr, ms, nl, no, pl, pt, ro, ru, sk, sl, sq, sr, sv, sw, te, th, tl, tr, uk, ur, uz, vi, zh → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Quantization formatquant_format1

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

File sizefile_size_gb1

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

Hugging Face repohf_repo1

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ibm-granite/granite-embedding-311m-multilingual-r2 → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Pipeline tagpipeline_tag1

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feature-extraction → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Model cardmodel_card_url1

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https://huggingface.co/ibm-granite/granite-embedding-311m-multilingual-r2 → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Downloadsmetric.downloads1

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120,372 → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Likesmetric.likes1

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

Gatedgated1

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ValueValid from → toStatusSourceConfidenceExtractor
No → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Hf inference providershf_inference_providers1

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

Is quantizedis_quantized1

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Yes → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Last modifiedlast_modified1

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ValueValid from → toStatusSourceConfidenceExtractor
2026-05-18T20:15:41+00:00 → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Library namelibrary_name1

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

Downloads all timemetric.downloads_all_time1

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ValueValid from → toStatusSourceConfidenceExtractor
721,749 → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Model typemodel_type1

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

Tagstags1

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ValueValid from → toStatusSourceConfidenceExtractor
sentence-transformers, onnx, safetensors, openvino, modernbert, feature-extraction, granite, embeddings, transformers, multilingual, mteb, sentence-similarity, matryoshka, ar, az, bg, bn, ca, cs, da, de, el, en, es, et, fa, fi, fr, he, hi → currentcurrentHugging Face Hub (public pages, model cards, papers)T2mediumdeterministic

Weights dtypeweights_dtype1

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ValueValid from → toStatusSourceConfidenceExtractor
BF16 → currentcurrentHugging 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

22

Source tiers

T222

Freshest observation

10 h ago

Conflicts

None

Source documents 3

Source documents
SourceDocumentTypeTierLast observedSnapshots
Hugging Face Hub (public pages, model cards, papers)huggingface.co/ibm-granite/granite-embedding-311m-multilingual-r2 model_pageT2· Quality secondary10 h ago3
Hugging Face Hub (public pages, model cards, papers)huggingface.co/models?author=ibm-granite&p=0&sort=downloads listingT2· Quality secondary10 h ago3
Hugging Face Hub (public pages, model cards, papers)huggingface.co/ibm-granite/granite-embedding-311m-multilingual-r2/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 →