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SAVRN Model Hub · Comparisons

embeddinggemma-300m vs paraphrase-multilingual-mpnet-base-v2

Embeddinggemma-300m has 303M parameters and paraphrase-multilingual-mpnet-base-v2 has 278M parameters; embeddinggemma-300m is released under Gemma Terms of Use and paraphrase-multilingual-mpnet-base-v2 under Apache License 2.0; at 16-bit, embeddinggemma-300m needs about 0.7 GB (1x MI300X from $1.85 an hour) and paraphrase-multilingual-mpnet-base-v2 about 0.7 GB (1x MI300X from $1.85 an hour).

Published metadata for 2 models, each read from its own repository.
Field embeddinggemma-300m
google/embeddinggemma-300m
paraphrase-multilingual-mpnet-base-v2
sentence-transformers/paraphrase-multilingual-mpnet-base-v2
Publisher Google Sentence Transformers
Task Sentence similarity Sentence similarity
Modality Text Text
Parameters, as reported 303M parameters 278M parameters
Architecture Gemma3TextModel XLMRobertaModel
Library sentence-transformers sentence-transformers
Context length Not stated 514 tokens
Repository size 1.3 GB 10.9 GB
Artifact formats safetensors safetensors, onnx, openvino, pytorch, tf
License gemma apache-2.0
Access Access requested at publisher Open weights, no gate
Memory at 16-bit (weights and margin) 0.7 GB 0.7 GB
Cheapest GPUs at 16-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Memory at 4-bit (weights and margin) 0.2 GB 0.2 GB
Cheapest GPUs at 4-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Revision viewed 57c266a740f5 4328cf26390c
Downloads reported by the hub 2.6M 9.8M
Last observed 2026-09-18 2026-09-18

An evaluation row appears only where at least two of these models report the same benchmark with the same stated configuration, metric, unit and setup. Different evaluators stay named in each cell. Values are shown as reported: no unit conversion, no ranking.

Other Reported Results

These results are listed for each model on its own, because the conditions needed to compare them are not stated or do not match. Two results that leave a condition blank are not assumed to share it.

embeddinggemma-300m

BenchmarkConditionsResultReported byRevisionDate
mteb/arguana Task ArguAnaMetric ArguAnaSetup Obtained using MTEB v1.34.7Comparison conditions not established 71.535 Obtained using MTEB v1.34.7
Reported by a third party
Evaluated revision not stated 2026-03-05
mteb/arguana Task ArguAna_default_testMetric ArguAna_default_testSetup Obtained using MTEB v1.34.7Comparison conditions not established 71.535 Obtained using MTEB v1.34.7
Reported by a third party
Evaluated revision not stated 2026-03-05

paraphrase-multilingual-mpnet-base-v2

BenchmarkConditionsResultReported byRevisionDate
mteb/arguana Task ArguAnaMetric ArguAnaSetup Obtained using MTEB v1.12.75Comparison conditions not established 48.908 Obtained using MTEB v1.12.75
Reported by a third party
Evaluated revision not stated 2026-03-05
mteb/arguana Task ArguAna_default_testMetric ArguAna_default_testSetup Obtained using MTEB v1.12.75Comparison conditions not established 48.908 Obtained using MTEB v1.12.75
Reported by a third party
Evaluated revision not stated 2026-03-05

SAVRN's Notes on embeddinggemma-300m

Retrieval is where this one earns its place: every document indexed and every query served passes through it, and at 0.7 GB of memory at 16-bit, EmbeddingGemma-300m never justifies a GPU on its own. Google built it from Gemma 3 and aimed it at phones, laptops and desktops, so share a card with the generator, or skip the GPU. The Index floor, one MI300X with 192 GB at $1.85 per hour, is a card you would barely touch.

Read the license twice. Gemma Terms of Use allow commercial use and redistribution only subject to the Gemma Prohibited Use Policy, and those restrictions pass to anyone you distribute it to, a flow-down obligation for any product built on it. Access is gated; the publisher grants it before the 19 files arrive. No context length is listed, so test your chunk size against the checkpoint dated September 25, 2025.

Questions

Which is larger, embeddinggemma-300m or paraphrase-multilingual-mpnet-base-v2?

embeddinggemma-300m (303M parameters) is larger than paraphrase-multilingual-mpnet-base-v2 (278M parameters), by the parameter counts their publishers report.

Which is cheaper to run, embeddinggemma-300m or paraphrase-multilingual-mpnet-base-v2?

At 4-bit, embeddinggemma-300m fits on 1x MI300X from $1.85 an hour and paraphrase-multilingual-mpnet-base-v2 on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use embeddinggemma-300m commercially?

Yes, with conditions. embeddinggemma-300m is released under Gemma Terms of Use. Gemma models are released under Google's Gemma Terms of Use, which permit commercial use and redistribution subject to the Gemma Prohibited Use Policy, whose restrictions must be passed on to anyone the model is distributed to.

Can I use paraphrase-multilingual-mpnet-base-v2 commercially?

Yes. paraphrase-multilingual-mpnet-base-v2 is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

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