SAVRN Model Hub · Comparisons
ms-marco-MiniLM-L2-v2 vs ms-marco-MiniLM-L4-v2
Ms-marco-MiniLM-L2-v2 has 16M parameters and ms-marco-MiniLM-L4-v2 has 19M parameters; both are released under Apache License 2.0; at 16-bit, ms-marco-MiniLM-L2-v2 needs about 0 GB (1x MI300X from $1.85 an hour) and ms-marco-MiniLM-L4-v2 about 0 GB (1x MI300X from $1.85 an hour).
| Field | ms-marco-MiniLM-L2-v2 cross-encoder/ms-marco-MiniLM-L2-v2 | ms-marco-MiniLM-L4-v2 cross-encoder/ms-marco-MiniLM-L4-v2 |
|---|---|---|
| Publisher | Sentence Transformers - Cross-Encoders | Sentence Transformers - Cross-Encoders |
| Task | Text ranking | Text ranking |
| Modality | Other | Other |
| Parameters, as reported | 16M parameters | 19M parameters |
| Architecture | BertForSequenceClassification | BertForSequenceClassification |
| Library | sentence-transformers | sentence-transformers |
| Context length | 512 tokens | 512 tokens |
| Repository size | 611.3 MB | 750.7 MB |
| Artifact formats | safetensors, onnx, openvino, pytorch, jax | safetensors, onnx, openvino, pytorch, jax |
| License | apache-2.0 | apache-2.0 |
| Access | Open weights, no gate | Open weights, no gate |
| Memory at 16-bit (weights and margin) | 0 GB | 0 GB |
| Cheapest GPUs at 16-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Memory at 4-bit (weights and margin) | 0 GB | 0 GB |
| Cheapest GPUs at 4-bit, per hour | 1x MI300X, $1.85 | 1x MI300X, $1.85 |
| Revision viewed | 1b5cd67b1520 | 777b2f369bc1 |
| Downloads reported by the hub | 430.9k | 4.8M |
| 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 ms-marco-MiniLM-L2-v2
Between the retriever and whatever reads the results is where this one lives: take a query, score it against every candidate passage a system like ElasticSearch pulled back, and sort them. At 16 million parameters and 2 layers, the memory line reads 0.0 GB at every precision, so the hardware decision is a placement decision. The cheapest setup we price is one MI300X with 192 GB at $1.85 an hour, though something this small belongs as a tenant beside a larger workload.
Apache 2.0 applies, so commercial use, modification and redistribution are fine with the notices kept and changes stated. The number to check is 512: that is the context length, and the query and passage go in together, so long passages need chunking upstream. On lineage, this 2-layer model is derived from cross-encoder/ms-marco-MiniLM-L12-v2 and trained on sentence-transformers/msmarco, so compare the L12 version before settling on the smaller one.
Questions
Which is larger, ms-marco-MiniLM-L2-v2 or ms-marco-MiniLM-L4-v2?
ms-marco-MiniLM-L4-v2 (19M parameters) is larger than ms-marco-MiniLM-L2-v2 (16M parameters), by the parameter counts their publishers report.
Which is cheaper to run, ms-marco-MiniLM-L2-v2 or ms-marco-MiniLM-L4-v2?
At 4-bit, ms-marco-MiniLM-L2-v2 fits on 1x MI300X from $1.85 an hour and ms-marco-MiniLM-L4-v2 on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use ms-marco-MiniLM-L2-v2 commercially?
Yes. ms-marco-MiniLM-L2-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 ms-marco-MiniLM-L4-v2 commercially?
Yes. ms-marco-MiniLM-L4-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.