SAVRN Model Hub · Comparisons
bert-base-multilingual-cased vs bert-base-multilingual-uncased
Bert-base-multilingual-cased has 179M parameters and bert-base-multilingual-uncased has 168M parameters; both are released under Apache License 2.0; at 16-bit, bert-base-multilingual-cased needs about 0.4 GB (1x MI300X from $1.85 an hour) and bert-base-multilingual-uncased about 0.4 GB (1x MI300X from $1.85 an hour).
| Field | bert-base-multilingual-cased google-bert/bert-base-multilingual-cased | bert-base-multilingual-uncased google-bert/bert-base-multilingual-uncased |
|---|---|---|
| Publisher | BERT community | BERT community |
| Task | Fill mask | Fill mask |
| Modality | Text | Text |
| Parameters, as reported | 179M parameters | 168M parameters |
| Architecture | BertForMaskedLM | BertForMaskedLM |
| Library | transformers | transformers |
| Context length | 512 tokens | 512 tokens |
| Repository size | 3.2 GB | 3.0 GB |
| Artifact formats | safetensors, pytorch, jax, tf | safetensors, pytorch, jax, tf |
| License | apache-2.0 | apache-2.0 |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 0.4 GB | 0.4 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 | 3f076fdb1ab6 | 7cbf9a625e29 |
| Downloads reported by the hub | 1.9M | 4M |
| Last observed | 2026-09-19 | 2026-09-19 |
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 bert-base-multilingual-cased
Nothing in the memory line will drive a hardware decision. The 16-bit weights are 0.4 GB and the model needs 0.4 GB to run; 8-bit takes 0.2 GB and 4-bit 0.1 GB, so the cheapest setup we list, one MI300X with 192 GB at $1.85 an hour on-demand, is priced for a different class of model. It predicts masked words, case-sensitive, in the 104 languages with the largest Wikipedias, and the hardware question is throughput per dollar, not fit.
Apache 2.0 clears commercial use, modification and redistribution; keep the license, the copyright notices and any NOTICE file, and state significant changes. Three checks before you build on it. The 512-token context caps passage length. The only training data on record is Wikipedia. And the repository holds 3.2 GB across four formats, safetensors, pytorch, jax and tf, when the 16-bit weights you need are 0.4 GB.
SAVRN's Notes on bert-base-multilingual-uncased
Four tenths of a gigabyte in 16-bit. For a 168M-parameter fill-mask model that number settles the hardware question: the cheapest setup we list, one MI300X with 192 GB at $1.85 an hour, would sit nearly idle, so put it on a card you already own as a tenant, or run 8-bit at 0.2 GB. It reads 512 tokens per pass, was pretrained on the 102 largest Wikipedia languages, and is uncased, so english and English look the same to it.
Apache 2.0 clears commercial use and redistribution provided the license, copyright notices and any NOTICE file stay attached and significant changes are stated. The 3.0 GB download spans 10 files in four formats, safetensors, pytorch, jax and tf, and you need only one. The card was written by someone other than the team that released the weights, so the paper, arXiv:1810.04805, is the source to read.
Questions
Which is larger, bert-base-multilingual-cased or bert-base-multilingual-uncased?
bert-base-multilingual-cased (179M parameters) is larger than bert-base-multilingual-uncased (168M parameters), by the parameter counts their publishers report.
Which is cheaper to run, bert-base-multilingual-cased or bert-base-multilingual-uncased?
At 4-bit, bert-base-multilingual-cased fits on 1x MI300X from $1.85 an hour and bert-base-multilingual-uncased on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use bert-base-multilingual-cased commercially?
Yes. bert-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 bert-base-multilingual-uncased commercially?
Yes. bert-base-multilingual-uncased 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.