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SAVRN Model Hub · Comparisons

distilbert-base-multilingual-cased vs roberta-base

Distilbert-base-multilingual-cased has 135M parameters and roberta-base has 125M parameters; distilbert-base-multilingual-cased is released under Apache License 2.0 and roberta-base under MIT License; at 16-bit, distilbert-base-multilingual-cased needs about 0.3 GB (1x MI300X from $1.85 an hour) and roberta-base about 0.3 GB (1x MI300X from $1.85 an hour).

Published metadata for 2 models, each read from its own repository.
Field distilbert-base-multilingual-cased
distilbert/distilbert-base-multilingual-cased
roberta-base
FacebookAI/roberta-base
Publisher DistilBERT community Facebook AI community
Task Fill mask Fill mask
Modality Text Text
Parameters, as reported 135M parameters 125M parameters
Architecture DistilBertForMaskedLM RobertaForMaskedLM
Library transformers transformers
Context length 512 tokens 514 tokens
Repository size 2.9 GB 2.8 GB
Artifact formats safetensors, onnx, pytorch, tf safetensors, pytorch, jax, rust, tf
License apache-2.0 mit
Access Open weights, no gate Open weights, no gate
Memory at 16-bit (weights and margin) 0.3 GB 0.3 GB
Cheapest GPUs at 16-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Memory at 4-bit (weights and margin) 0.1 GB 0.1 GB
Cheapest GPUs at 4-bit, per hour 1x MI300X, $1.85 1x MI300X, $1.85
Revision viewed 45c032ab32cc e2da8e2f811d
Downloads reported by the hub 541.6k 7.9M
Last observed 2026-09-18 2026-10-16

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.

SAVRN's Notes on distilbert-base-multilingual-cased

This is the distilled version of multilingual BERT: one encoder that covers the Wikipedia languages it was trained on, at 135M parameters and noticeably faster than the original. It is cased, so it treats capitalization as meaningful, which helps with names and acronyms.

It is a base model for fine-tuning, not a finished classifier. Apache 2.0 allows commercial use. For new multilingual work, compare it with XLM-RoBERTa and mDeBERTa-v3 base in our catalog, which usually fine-tune to higher accuracy; keep DistilBERT where speed per request matters most.

SAVRN's Notes on roberta-base

Case matters here: roberta-base, from the Facebook AI community, tells english from English. Pretrained on raw English text from bookcorpus and wikipedia by masked language modeling, its listed task is fill mask: token prediction and what you build on it, not chat. At 16-bit its 125M parameters take 0.2 GB of weights and 0.3 GB to run, against a cheapest listed setup of one 192 GB MI300X at $1.85 per hour on-demand; on our floor that shares a card, never owns one.

MIT is short: commercial use, modification and redistribution are allowed, the one duty being to carry the copyright and permission notices along. Check provenance and packaging. The releasing team wrote no model card, so bookcorpus and wikipedia are all the page discloses on data. The repository is 2.82 GB across 13 files in safetensors, pytorch, jax, rust and tf; pull only the format your stack loads.

Questions

Which is larger, distilbert-base-multilingual-cased or roberta-base?

distilbert-base-multilingual-cased (135M parameters) is larger than roberta-base (125M parameters), by the parameter counts their publishers report.

Which is cheaper to run, distilbert-base-multilingual-cased or roberta-base?

At 4-bit, distilbert-base-multilingual-cased fits on 1x MI300X from $1.85 an hour and roberta-base on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use distilbert-base-multilingual-cased commercially?

Yes. distilbert-base-multilingual-cased 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.

Can I use roberta-base commercially?

Yes. roberta-base is released under MIT License. The MIT License is a short permissive license. It permits commercial use, modification and redistribution, provided the copyright notice and permission notice are included.

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