SAVRN Model Hub · Comparisons
CLIP-ViT-L-14-laion2B-s32B-b82K vs clip-vit-large-patch14
CLIP-ViT-L-14-laion2B-s32B-b82K has 428M parameters and clip-vit-large-patch14 has 428M parameters; at 16-bit, CLIP-ViT-L-14-laion2B-s32B-b82K needs about 1 GB (1x MI300X from $1.85 an hour) and clip-vit-large-patch14 about 1 GB (1x MI300X from $1.85 an hour).
| Field | CLIP-ViT-L-14-laion2B-s32B-b82K laion/CLIP-ViT-L-14-laion2B-s32B-b82K | clip-vit-large-patch14 openai/clip-vit-large-patch14 |
|---|---|---|
| Publisher | LAION eV | OpenAI |
| Task | Zero shot image classification | Zero shot image classification |
| Modality | Other | Other |
| Parameters, as reported | 428M parameters | 428M parameters |
| Architecture | CLIPModel | CLIPModel |
| Library | open_clip | transformers |
| Context length | 77 tokens | 77 tokens |
| Repository size | 6.8 GB | 6.8 GB |
| Artifact formats | safetensors, pytorch, tensorboard | safetensors, pytorch, jax, tf |
| License | mit | Not stated |
| 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) | 0.3 GB | 0.3 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 162703219714 | 32bd64288804 |
| Downloads reported by the hub | 4M | 8.3M |
| 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 CLIP-ViT-L-14-laion2B-s32B-b82K
Hand it a photo and a few label phrases you just wrote, and it tells you which phrase fits, with no training run; that is zero-shot image classification. The text side stops at 77 tokens, so labels are phrases, not paragraphs. At 16-bit the 428M parameters weigh 0.9 GB and the run needs 1.0 GB, a rounding error on the 192 GB MI300X we price at $1.85 an hour, so it shares a card rather than owning one.
MIT permits commercial use, modification and redistribution with the notices kept, but weigh the publisher's framing too: LAION eV calls this a research output for research communities, trained on the LAION-2B English subset of LAION-5B with OpenCLIP. Before committing, run that data lineage through your governance review, check that English training text suits your labels, and decide whether a checkpoint released September 14, 2022 is current enough for your pipeline.
SAVRN's Notes on clip-vit-large-patch14
The text side of this model stops at 77 tokens, which tells you what it is for: scoring images against short text labels, the zero-shot classification OpenAI built it to study, not reading documents. On disk it is 6.85 GB across 13 files, float32 in four formats, but loaded at 16-bit it needs 1.0 GB and at 4-bit 0.3 GB. The cheapest setup we list, one 192 GB MI300X at $1.85 per hour on-demand, is a card you would share; the question is throughput, not fit.
Our record carries no license for it; that is the first check: get the terms from the publisher's files before commercial use. The second is the card's warning that it was not developed for general deployment; study it in your context, and if faces are in your images, start with the FairFace paper on race, gender and age the record ties it to.
Questions
Which is larger, CLIP-ViT-L-14-laion2B-s32B-b82K or clip-vit-large-patch14?
CLIP-ViT-L-14-laion2B-s32B-b82K (428M parameters) is larger than clip-vit-large-patch14 (428M parameters), by the parameter counts their publishers report.
Which is cheaper to run, CLIP-ViT-L-14-laion2B-s32B-b82K or clip-vit-large-patch14?
At 4-bit, CLIP-ViT-L-14-laion2B-s32B-b82K fits on 1x MI300X from $1.85 an hour and clip-vit-large-patch14 on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use CLIP-ViT-L-14-laion2B-s32B-b82K commercially?
Yes. CLIP-ViT-L-14-laion2B-s32B-b82K 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.