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SAVRN Model Hub · Comparisons

bge-base-en-v1.5-course-recommender-v5 vs e5-base-v2

Bge-base-en-v1.5-course-recommender-v5 has 109M parameters and e5-base-v2 has 109M parameters; at 16-bit, bge-base-en-v1.5-course-recommender-v5 needs about 0.3 GB (1x MI300X from $1.85 an hour) and e5-base-v2 about 0.3 GB (1x MI300X from $1.85 an hour).

Published metadata for 2 models, each read from its own repository.
Field bge-base-en-v1.5-course-recommender-v5
datasocietyco/bge-base-en-v1.5-course-recommender-v5
e5-base-v2
intfloat/e5-base-v2
Publisher Data Society Liang Wang
Task Sentence similarity Sentence similarity
Modality Text Text
Parameters, as reported 109M parameters 109M parameters
Architecture BertModel BertModel
Library sentence-transformers sentence-transformers
Context length 512 tokens 512 tokens
Repository size 438.9 MB 2.2 GB
Artifact formats safetensors safetensors, onnx, openvino, pytorch
License Not stated mit
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 2b069eed51ce f52bf8ec8c71
Downloads reported by the hub 4.2M 890.2k
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.

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.

e5-base-v2

BenchmarkConditionsResultReported byRevisionDate
MTEB AmazonCounterfactualClassification (en) Configuration enTask ClassificationMetric accuracyComparison conditions not established 77.7761 intfloat
Publisher reported
Evaluated revision not stated
MTEB AmazonCounterfactualClassification (en) Configuration enTask ClassificationMetric apComparison conditions not established 42.0527 intfloat
Publisher reported
Evaluated revision not stated
MTEB AmazonCounterfactualClassification (en) Configuration enTask ClassificationMetric f1Comparison conditions not established 72.1204 intfloat
Publisher reported
Evaluated revision not stated
MTEB AmazonPolarityClassification Configuration defaultTask ClassificationMetric accuracyComparison conditions not established 92.8101 intfloat
Publisher reported
Evaluated revision not stated
MTEB AmazonPolarityClassification Configuration defaultTask ClassificationMetric apComparison conditions not established 89.4214 intfloat
Publisher reported
Evaluated revision not stated
MTEB AmazonPolarityClassification Configuration defaultTask ClassificationMetric f1Comparison conditions not established 92.8039 intfloat
Publisher reported
Evaluated revision not stated
MTEB AmazonReviewsClassification (en) Configuration enTask ClassificationMetric accuracyComparison conditions not established 46.712 intfloat
Publisher reported
Evaluated revision not stated
MTEB AmazonReviewsClassification (en) Configuration enTask ClassificationMetric f1Comparison conditions not established 46.1154 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric map_at_1Comparison conditions not established 23.186 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric map_at_10Comparison conditions not established 36.633 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric map_at_100Comparison conditions not established 37.842 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric map_at_1000Comparison conditions not established 37.865 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric map_at_3Comparison conditions not established 32.278 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric map_at_5Comparison conditions not established 34.761 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric mrr_at_1Comparison conditions not established 23.4 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric mrr_at_10Comparison conditions not established 36.721 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric mrr_at_100Comparison conditions not established 37.937 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric mrr_at_1000Comparison conditions not established 37.96 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric mrr_at_3Comparison conditions not established 32.302 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric mrr_at_5Comparison conditions not established 34.894 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric ndcg_at_1Comparison conditions not established 23.186 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric ndcg_at_10Comparison conditions not established 44.49 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric ndcg_at_100Comparison conditions not established 50.065 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric ndcg_at_1000Comparison conditions not established 50.63 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric ndcg_at_3Comparison conditions not established 35.461 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric ndcg_at_5Comparison conditions not established 39.969 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric precision_at_1Comparison conditions not established 23.186 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric precision_at_10Comparison conditions not established 6.97 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric precision_at_100Comparison conditions not established 0.951 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric precision_at_1000Comparison conditions not established 0.099 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric precision_at_3Comparison conditions not established 14.912 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric precision_at_5Comparison conditions not established 11.152 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric recall_at_1Comparison conditions not established 23.186 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric recall_at_10Comparison conditions not established 69.701 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric recall_at_100Comparison conditions not established 95.092 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric recall_at_1000Comparison conditions not established 99.431 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric recall_at_3Comparison conditions not established 44.737 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArguAna Configuration defaultTask RetrievalMetric recall_at_5Comparison conditions not established 55.761 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArxivClusteringP2P Configuration defaultTask ClusteringMetric v_measureComparison conditions not established 46.1031 intfloat
Publisher reported
Evaluated revision not stated
MTEB ArxivClusteringS2S Configuration defaultTask ClusteringMetric v_measureComparison conditions not established 39.6728 intfloat
Publisher reported
Evaluated revision not stated

SAVRN's Notes on bge-base-en-v1.5-course-recommender-v5

The name tells you the target. Data Society tuned this model to recommend courses, and the entire fine-tune from the BAAI/bge-base-en-v1.5 it derives from is 24 training steps at a batch size of 16 and a learning rate of 3e-06. Each input becomes a 768-dimensional vector for similarity search and clustering. The 16-bit working set is 0.3 GB, the download 439 MB, and the cheapest listed setup, one MI300X with 192 GB at $1.85 an hour, uses well under one percent of the card.

No license is recorded on this fine-tune, so settle that first with the publisher before these vectors go into a production index. Then run the base alongside it: 24 steps is a light touch, and you want to measure what it changed on your own catalog. Inputs stop at 512 tokens, the stored weights are float32, and the method traces to arXiv:1908.10084 and arXiv:1705.00652.

SAVRN's Notes on e5-base-v2

Every passage this embedding model sees is capped at 512 tokens, so chunking comes before hardware. Liang Wang published it as a 109 million parameter BertModel with 12 layers and a 768-wide embedding, built for sentence similarity; it runs in 0.3 GB of memory at 16-bit and 0.1 GB at 8-bit. The cheapest setup on our Index is one MI300X with 192 GB at $1.85 per hour, so the card is bought for throughput, not weights. The 2.19 GB download across 24 files carries four formats, safetensors, ONNX, OpenVINO and PyTorch, so load one.

MIT terms allow commercial use, modification and redistribution with the notices kept, so an index built on it can ship inside a product. Note that the benchmark results in the file are publisher reported, such as 92.81 accuracy on MTEB AmazonPolarityClassification, and the method sits in arXiv:2212.03533; test retrieval on your own corpus.

Questions

Which is larger, bge-base-en-v1.5-course-recommender-v5 or e5-base-v2?

e5-base-v2 (109M parameters) is larger than bge-base-en-v1.5-course-recommender-v5 (109M parameters), by the parameter counts their publishers report.

Which is cheaper to run, bge-base-en-v1.5-course-recommender-v5 or e5-base-v2?

At 4-bit, bge-base-en-v1.5-course-recommender-v5 fits on 1x MI300X from $1.85 an hour and e5-base-v2 on 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use e5-base-v2 commercially?

Yes. e5-base-v2 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.

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