SAVRN Model Hub · Comparisons
esm2_t33_650M_UR50D vs xlm-roberta-large
Esm2_t33_650M_UR50D has 652M parameters and xlm-roberta-large has 561M parameters; both are released under MIT License; at 16-bit, esm2_t33_650M_UR50D needs about 1.6 GB (1x MI300X from $1.85 an hour) and xlm-roberta-large about 1.3 GB (1x MI300X from $1.85 an hour).
| Field | esm2_t33_650M_UR50D facebook/esm2_t33_650M_UR50D | xlm-roberta-large FacebookAI/xlm-roberta-large |
|---|---|---|
| Publisher | AI at Meta | Facebook AI community |
| Task | Fill mask | Fill mask |
| Modality | Text | Text |
| Parameters, as reported | 652M parameters | 561M parameters |
| Architecture | EsmForMaskedLM | XLMRobertaForMaskedLM |
| Library | transformers | transformers |
| Context length | 1,026 tokens | 514 tokens |
| Repository size | 7.8 GB | 11.2 GB |
| Artifact formats | safetensors, pytorch, tf | safetensors, onnx, pytorch, jax, tf |
| License | mit | mit |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 1.6 GB | 1.3 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 0.4 GB | 0.3 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 08e4846e5371 | c23d21b0620b |
| Downloads reported by the hub | 1.5M | 3.2M |
| 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.
SAVRN's Notes on esm2_t33_650M_UR50D
AI at Meta built this checkpoint for teams that fine-tune on protein sequences, and the numbers say it will never fill an accelerator. Serving one copy takes 1.6 GB at 16-bit, 0.8 GB at 8-bit, or 0.4 GB at 4-bit. The cheapest Index listing at every precision is one MI300X with 192 GB at $1.85 per hour, so a single instance would use less than one percent of the card. Stack fine-tuning jobs or parallel copies on that one device rather than dedicating it.
The MIT license permits commercial use, modification and redistribution provided the copyright and permission notices ship with the files, so a fine-tuned variant is clear for a commercial product. Two checks before committing: the window is 1,026 tokens per sequence, and the download is 7.8 GB across nine files, stored in float32 in safetensors, pytorch and tf formats, so pull only the format your stack loads.
SAVRN's Notes on xlm-roberta-large
Fitting this one is never the problem. At 16-bit the weights are 1.1 GB and the run needs 1.3 GB, so the cheapest setup on the page, one 192 GB MI300X at $1.85 an hour on-demand, has room for more than a hundred copies; put it on a GPU already serving something else. What the footprint buys is a fill-mask model trained on 2.5 TB of filtered CommonCrawl in 100 languages with a 250,002-entry vocabulary: a starting layer for multilingual text work you tune yourself, not a finished application.
MIT asks only that the copyright and permission notice travel with what you ship; commercial use, modification and redistribution are allowed. Note the 514-token context, sentences and short passages rather than documents, and the 17 files totaling 11.2 GB across five formats, of which your runtime needs one. The releasing team did not write the card; start from arXiv 1911.02116.
Questions
Which is larger, esm2_t33_650M_UR50D or xlm-roberta-large?
esm2_t33_650M_UR50D (652M parameters) is larger than xlm-roberta-large (561M parameters), by the parameter counts their publishers report.
Which is cheaper to run, esm2_t33_650M_UR50D or xlm-roberta-large?
At 4-bit, esm2_t33_650M_UR50D fits on 1x MI300X from $1.85 an hour and xlm-roberta-large on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use esm2_t33_650M_UR50D commercially?
Yes. esm2_t33_650M_UR50D 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.
Can I use xlm-roberta-large commercially?
Yes. xlm-roberta-large 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.