SAVRN Model Hub · Comparisons
distiluse-base-multilingual-cased-v2 vs nomic-embed-text-v1.5
Distiluse-base-multilingual-cased-v2 has 135M parameters and nomic-embed-text-v1.5 has 137M parameters; both are released under Apache License 2.0; at 16-bit, distiluse-base-multilingual-cased-v2 needs about 0.3 GB (1x MI300X from $1.85 an hour) and nomic-embed-text-v1.5 about 0.3 GB (1x MI300X from $1.85 an hour).
| Field | distiluse-base-multilingual-cased-v2 sentence-transformers/distiluse-base-multilingual-cased-v2 | nomic-embed-text-v1.5 nomic-ai/nomic-embed-text-v1.5 |
|---|---|---|
| Publisher | Sentence Transformers | Nomic AI |
| Task | Sentence similarity | Sentence similarity |
| Modality | Text | Text |
| Parameters, as reported | 135M parameters | 137M parameters |
| Architecture | DistilBertModel | NomicBertModel |
| Library | sentence-transformers | sentence-transformers |
| Context length | 512 tokens | 2,048 tokens |
| Repository size | 5.3 GB | 2.2 GB |
| Artifact formats | safetensors, onnx, openvino, pytorch, tf | safetensors, onnx |
| License | apache-2.0 | apache-2.0 |
| 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 | bfe45d0732ca | e9b6763023c6 |
| Downloads reported by the hub | 1M | 13.2M |
| Last observed | 2026-09-28 | 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.
Other Reported Results
These results are listed for each model on its own, because the conditions needed to compare them are not stated or do not match. Two results that leave a condition blank are not assumed to share it.
nomic-embed-text-v1.5
| Benchmark | Conditions | Result | Reported by | Revision | Date |
|---|---|---|---|---|---|
| MTEB AmazonCounterfactualClassification (en) | Configuration enTask ClassificationMetric accuracyComparison conditions not established | 75.209 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB AmazonCounterfactualClassification (en) | Configuration enTask ClassificationMetric apComparison conditions not established | 38.5761 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB AmazonCounterfactualClassification (en) | Configuration enTask ClassificationMetric f1Comparison conditions not established | 69.3559 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB AmazonPolarityClassification | Configuration defaultTask ClassificationMetric accuracyComparison conditions not established | 91.8144 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB AmazonPolarityClassification | Configuration defaultTask ClassificationMetric apComparison conditions not established | 88.6522 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB AmazonPolarityClassification | Configuration defaultTask ClassificationMetric f1Comparison conditions not established | 91.8043 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB AmazonReviewsClassification (en) | Configuration enTask ClassificationMetric accuracyComparison conditions not established | 47.162 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB AmazonReviewsClassification (en) | Configuration enTask ClassificationMetric f1Comparison conditions not established | 46.5933 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_1Comparison conditions not established | 24.253 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_10Comparison conditions not established | 38.962 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_100Comparison conditions not established | 40.081 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_1000Comparison conditions not established | 40.089 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_3Comparison conditions not established | 33.499 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_5Comparison conditions not established | 36.351 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_1Comparison conditions not established | 24.609 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_10Comparison conditions not established | 39.099 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_100Comparison conditions not established | 40.211 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_1000Comparison conditions not established | 40.219 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_3Comparison conditions not established | 33.677 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_5Comparison conditions not established | 36.469 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_1Comparison conditions not established | 24.253 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_10Comparison conditions not established | 48.011 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_100Comparison conditions not established | 52.756 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_1000Comparison conditions not established | 52.965 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_3Comparison conditions not established | 36.564 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_5Comparison conditions not established | 41.712 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_1Comparison conditions not established | 24.253 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_10Comparison conditions not established | 7.738 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_100Comparison conditions not established | 0.98 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_1000Comparison conditions not established | 0.1 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_3Comparison conditions not established | 15.149 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_5Comparison conditions not established | 11.593 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_1Comparison conditions not established | 24.253 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_10Comparison conditions not established | 77.383 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_100Comparison conditions not established | 98.009 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_1000Comparison conditions not established | 99.644 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_3Comparison conditions not established | 45.448 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_5Comparison conditions not established | 57.966 | nomic-ai Publisher reported |
Evaluated revision not stated | — |
| mteb/arguana | Task ArguAnaMetric ArguAnaSetup Obtained using MTEB v1.18.0Comparison conditions not established | 52.018 | Obtained using MTEB v1.18.0 Reported by a third party |
Evaluated revision not stated | 2026-03-05 |
| mteb/arguana | Task ArguAna_default_testMetric ArguAna_default_testSetup Obtained using MTEB v1.18.0Comparison conditions not established | 52.018 | Obtained using MTEB v1.18.0 Reported by a third party |
Evaluated revision not stated | 2026-03-05 |
SAVRN's Notes on distiluse-base-multilingual-cased-v2
We keep encoders this size for jobs where a GPU is optional. At 135 million parameters and 0.3 gigabytes of memory at 16-bit, this multilingual sentence model fits in the corner of any accelerator, and the cheapest listed setup, one MI300X at $1.85 an hour, only makes sense as a sidecar to something larger on the same card. The format list matters more: safetensors, ONNX, OpenVINO, PyTorch and TensorFlow are all published, so it can run on CPU inference boxes where that hourly rate never applies. Output is a 512-dimensional vector per input.
Apache 2.0 permits commercial use, so it can ship inside a product with only the notices retained. Check two things: the 512-token context means long documents get chunked before embedding, and the repository is 30 files and 5.3 gigabytes across those formats, so pull only what your runtime needs. Its paper is Sentence-BERT, arXiv:1908.10084.
SAVRN's Notes on nomic-embed-text-v1.5
137M parameters, a 2,048-token context, 0.3 GB at 16-bit, 0.1 GB at 4-bit: this sentence embedder is a passenger on whatever card you already run. The files are the interesting part — nine weight builds including ONNX fp16, int8, uint8, bnb4, q4 and q4f16 alongside model.safetensors — so CPU and edge deployments are first-class rather than afterthought conversions. The cheapest setup we price is one 192 GB MI300X at $1.85 an hour.
Apache 2.0 permits commercial use with notices kept. Two operational details from the card: every input string needs a task instruction prefix — search_document: for corpus text, search_query: for queries — and the model is built on Matryoshka Representation Learning, so you can resize output dimensions to trade recall for footprint. Loaders older than transformers 5.5.0 and sentence-transformers 5.3.0 need trust_remote_code. A companion vision model shares the embedding space, so text and images can index together.
Questions
Which is larger, distiluse-base-multilingual-cased-v2 or nomic-embed-text-v1.5?
nomic-embed-text-v1.5 (137M parameters) is larger than distiluse-base-multilingual-cased-v2 (135M parameters), by the parameter counts their publishers report.
Which is cheaper to run, distiluse-base-multilingual-cased-v2 or nomic-embed-text-v1.5?
At 4-bit, distiluse-base-multilingual-cased-v2 fits on 1x MI300X from $1.85 an hour and nomic-embed-text-v1.5 on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use distiluse-base-multilingual-cased-v2 commercially?
Yes. distiluse-base-multilingual-cased-v2 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 nomic-embed-text-v1.5 commercially?
Yes. nomic-embed-text-v1.5 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.