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SAVRN Model Hub · Comparisons

bart-large-mnli vs ModernBERT-large-nli

Bart-large-mnli has 407M parameters and ModernBERT-large-nli has 396M parameters; bart-large-mnli is released under MIT License and ModernBERT-large-nli under Apache License 2.0; at 16-bit, bart-large-mnli needs about 1 GB (1x MI300X from $1.85 an hour) and ModernBERT-large-nli about 1 GB (1x MI300X from $1.85 an hour).

Published metadata for 2 models, each read from its own repository.
Field bart-large-mnli
facebook/bart-large-mnli
ModernBERT-large-nli
tasksource/ModernBERT-large-nli
Publisher AI at Meta Tasksource
Task Zero-shot classification Zero-shot classification
Modality Text Text
Parameters, as reported 407M parameters 396M parameters
Architecture BartForSequenceClassification ModernBertForSequenceClassification
Library transformers transformers
Context length 1,024 tokens 2,048 tokens
Repository size 6.9 GB 1.6 GB
Artifact formats safetensors, pytorch, jax, rust safetensors
License mit apache-2.0
Access Open weights, no gate Open weights, no gate
Memory at 16-bit (weights and margin) 1 GB 1 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 d7645e127eaf ca476cb923a8
Downloads reported by the hub 3.1M 21.1k
Last observed 2026-09-21 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 bart-large-mnli

Zero-shot here means the labels arrive at inference time, not training time. The passage becomes the premise, each candidate label becomes a hypothesis, and the entailment score picks the winner, so a ten-label job is ten passes over the same text and throughput, not memory, is what to plan around. The cheapest listed setup is a single MI300X, 192 GB, at $1.85 per hour on-demand; at 16-bit the 407 million parameters need 1.0 GB of it, so share the card.

The license is MIT: keep the copyright and permission notice and use, modify and redistribute it commercially as you like. Two checks. The context is 1,024 tokens, so long documents get chunked. And the lineage: this is bart-large after training on MultiNLI; arXiv 1910.13461 covers BART and arXiv 1909.00161 the zero-shot method. No host on our Index prices it by the token, so you run it yourself.

Questions

Which is larger, bart-large-mnli or ModernBERT-large-nli?

bart-large-mnli (407M parameters) is larger than ModernBERT-large-nli (396M parameters), by the parameter counts their publishers report.

Which is cheaper to run, bart-large-mnli or ModernBERT-large-nli?

At 4-bit, bart-large-mnli fits on 1x MI300X from $1.85 an hour and ModernBERT-large-nli on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use bart-large-mnli commercially?

Yes. bart-large-mnli 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 ModernBERT-large-nli commercially?

Yes. ModernBERT-large-nli 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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