# bge-base-en by Beijing Academy of Artificial Intelligence
Source: https://savrn.com/models/bge-base-en
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

---

## Runs On

What it takes to serve bge-base-en (109M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
| --- | --- | --- | --- | --- | --- |
| 16-bit | 0.2 GB | 0.3 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 8-bit | 0.1 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 4-bit | 0.1 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the [SAVRN Index](https://savrn.com/ai-index/pricing/gpus), read Oct 25, 2026.

[bge-base-en on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/bge-base-en/gpus)

## SAVRN's Notes on bge-base-en

The publisher's own page steers you to bge-base-en-v1.5 as the replacement, so the first question is why this one. Usually the answer is a vector store already built on it; re-embedding is the switching cost. The hardware numbers barely register: 109 million parameters, 0.2 GB of weights at 16-bit, 0.3 GB to run. A 192 GB MI300X at $1.85 an hour is wasted on this alone; we run models this size as a sidecar beside a generation model. The 512-token context is the binding limit; anything longer gets chunked.

MIT asks for one thing, the copyright and permission notice, and gives commercial use, modification and redistribution in return. The 1.3 GB download carries three formats, safetensors, ONNX and PyTorch, in float32, so pick one. And check the dates: released August 5, 2023, last updated April 17, 2024, and with the publisher pointing elsewhere this is a dependency you maintain yourself.

SAVRN Research, 2026-09-18

## Model Card

By Beijing Academy of Artificial Intelligence, published under mit, revision b737bf5dcc6e.

Recommend switching to newest [BAAI/bge-base-en-v1.5](https://savrn.com/models/bge-base-en-v1-5), which has more reasonable similarity distribution and same method of usage.

### FlagEmbedding

#### Model List | FAQ | Usage | Evaluation | Train | Contact | Citation | License

More details please refer to our Github: [FlagEmbedding](https://github.com/FlagOpen/FlagEmbedding).

English | [中文](https://github.com/FlagOpen/FlagEmbedding/blob/master/README_zh.md)

FlagEmbedding can map any text to a low-dimensional dense vector which can be used for tasks like retrieval, classification, clustering, or semantic search. And it also can be used in vector databases for LLMs.

[Read the full model card (2,409 words)](https://savrn.com/models/bge-base-en/card)

## Configuration

Architecture

BertModel

Context length (tokens)

512

Layers

12

Hidden size

768

Feed-forward size

3,072

Attention heads

12

Vocabulary size

30,522

Stored precision

float32

Model type

bert

## Identity and Version

Repository

BAAI/bge-base-en

Publisher

Beijing Academy of Artificial Intelligence

Task

Feature extraction

Modality

Text

Library

transformers

Parameters

109M parameters

Languages

en

Revision

b737bf5dcc6ee8bdc530531266b4804a5d77b5d8

First published

2023-08-05

Last updated

2024-04-17

## Files and Weights

19 files, 1.3 GB in total. The weights are 3 files totalling 1.3 GB in bin, onnx, safetensors.

Weights3 files · 1.3 GB

Configuration8 files · 3.0 KB

Tokenizer6 files · 1.9 MB

Documentation1 file · 90.1 KB

Repository1 file · 1.5 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| model.safetensors | Weights | 438.0 MB | 4628723bc592 |
| onnx/model.onnx | Weights | 435.8 MB | 2c3bee559d88 |
| pytorch_model.bin | Weights | 438.0 MB | 28fc2b964596 |
| 1_Pooling/config.json | Configuration | 190 B | — |
| config.json | Configuration | 719 B | — |
| config_sentence_transformers.json | Configuration | 124 B | — |
| modules.json | Configuration | 349 B | — |
| onnx/config.json | Configuration | 707 B | — |
| onnx/special_tokens_map.json | Configuration | 695 B | — |
| sentence_bert_config.json | Configuration | 52 B | — |
| special_tokens_map.json | Configuration | 125 B | — |
| README.md | Documentation | 90.1 KB | — |
| .gitattributes | Repository | 1.5 KB | — |
| onnx/tokenizer.json | Tokenizer | 711.4 KB | — |
| onnx/tokenizer_config.json | Tokenizer | 1.2 KB | — |
| onnx/vocab.txt | Tokenizer | 231.5 KB | — |
| tokenizer.json | Tokenizer | 711.4 KB | — |
| tokenizer_config.json | Tokenizer | 366 B | — |
| vocab.txt | Tokenizer | 231.5 KB | — |

## License and Download

License

mit

Access

Open weights, no gate

Download size

1.3 GB

[Download from Beijing Academy of Artificial Intelligence](https://huggingface.co/BAAI/bge-base-en)

Released by Beijing Academy of Artificial Intelligence through its official repository on Hugging Face. [Read the license](https://opensource.org/license/mit).

## Built From

- Described by [arXiv:2309.07597](https://savrn.com/papers/c-pack-packaged-resources-to-advance-general-chinese-embedding)
- Described by [arXiv:2310.07554](https://savrn.com/papers/retrieve-anything-to-augment-large-language-models)

## Evaluations

Each result is shown as reported, with the conditions its reporter stated. None is a SAVRN measurement. A comparison lines two results up only when their configuration, unit and setup are all stated and identical.

| Benchmark | Conditions | Result | Reported by | Revision | Date |
| --- | --- | --- | --- | --- | --- |
| MTEB AmazonCounterfactualClassification (en) | Configuration enTask ClassificationMetric accuracyComparison conditions not established | 75.7313 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB AmazonCounterfactualClassification (en) | Configuration enTask ClassificationMetric apComparison conditions not established | 38.9728 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB AmazonCounterfactualClassification (en) | Configuration enTask ClassificationMetric f1Comparison conditions not established | 69.8174 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB AmazonPolarityClassification | Configuration defaultTask ClassificationMetric accuracyComparison conditions not established | 92.5652 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB AmazonPolarityClassification | Configuration defaultTask ClassificationMetric apComparison conditions not established | 88.8882 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB AmazonPolarityClassification | Configuration defaultTask ClassificationMetric f1Comparison conditions not established | 92.5482 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB AmazonReviewsClassification (en) | Configuration enTask ClassificationMetric accuracyComparison conditions not established | 46.91 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB AmazonReviewsClassification (en) | Configuration enTask ClassificationMetric f1Comparison conditions not established | 46.2854 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_1Comparison conditions not established | 38.834 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_10Comparison conditions not established | 53.564 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_100Comparison conditions not established | 54.23 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_1000Comparison conditions not established | 54.235 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_3Comparison conditions not established | 49.49 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric map_at_5Comparison conditions not established | 51.784 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_1Comparison conditions not established | 39.26 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_10Comparison conditions not established | 53.744 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_100Comparison conditions not established | 54.41 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_1000Comparison conditions not established | 54.415 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_3Comparison conditions not established | 49.656 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric mrr_at_5Comparison conditions not established | 52.018 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_1Comparison conditions not established | 38.834 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_10Comparison conditions not established | 61.487 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_100Comparison conditions not established | 64.303 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_1000Comparison conditions not established | 64.408 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_3Comparison conditions not established | 53.116 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric ndcg_at_5Comparison conditions not established | 57.248 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_1Comparison conditions not established | 38.834 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_10Comparison conditions not established | 8.663 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_100Comparison conditions not established | 0.989 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_1000Comparison conditions not established | 0.1 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_3Comparison conditions not established | 21.219 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric precision_at_5Comparison conditions not established | 14.737 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_1Comparison conditions not established | 38.834 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_10Comparison conditions not established | 86.629 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_100Comparison conditions not established | 98.862 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_1000Comparison conditions not established | 99.644 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_3Comparison conditions not established | 63.656 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArguAna | Configuration defaultTask RetrievalMetric recall_at_5Comparison conditions not established | 73.684 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArxivClusteringP2P | Configuration defaultTask ClusteringMetric v_measureComparison conditions not established | 48.8848 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |
| MTEB ArxivClusteringS2S | Configuration defaultTask ClusteringMetric v_measureComparison conditions not established | 42.8505 | [BAAI](https://huggingface.co/BAAI/bge-base-en) Publisher reported | Evaluated revision not stated | — |

## Memory Requirements

| Precision | Weights in memory |
| --- | --- |
| As published | 1.3 GB |
| 16-bit | 0.2 GB |
| 8-bit | 0.1 GB |
| 4-bit | 0.1 GB |

Weights only, from the published parameter count; the key-value cache and runtime add to this.

## Questions About bge-base-en

### How much GPU memory does bge-base-en need?

About 0.3 GB at 16-bit and 0.1 GB at 4-bit: the weights (109M parameters) plus a working margin. A long context needs more.

### What is the cheapest GPU to run bge-base-en on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

### Can I use bge-base-en commercially?

Yes. bge-base-en 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.

### What is bge-base-en's context length?

512 tokens, from the maximum position embeddings in its published configuration.

## Similar Models

Model · Feature extraction

### [bge-base-en-v1.5](https://savrn.com/models/bge-base-en-v1-5)

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For more details please refer to our Github: FlagEmbedding. If you are looking for a model that supports more languages, longer texts, and other retrieval methods, you can try using bge-m3. FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently: - 1/30/2024: Release BGE-M3, a new member to BGE model series! M3 stands for Multi-linguality (100+ languages), Multi-granularities (input length up to 8192), Multi-Functionality (unification of dense, lexical, multi-vec/colbert retrieval). It is the first embedding model which supports all three retrieval methods, achieving new SOTA on multi-lingual (MIRACL) and cross-lingual (MKQA) benchmarks. Technical…

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Open weights apache-2.0 109M parameters 512 tokens transformers

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Open weights apache-2.0 121M parameters 262,144 tokens transformers

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This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Open weights 122M parameters transformers

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Model · Feature extraction

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## Beijing Academy of Artificial Intelligence

[All models and datasets](https://savrn.com/model-publishers/baai)

## Versions

- [b737bf5dcc6e](https://savrn.com/models/bge-base-en/versions/b737bf5dcc6e) · current 2026-10-25

## Explore More

- [All feature extraction models](https://savrn.com/models/tasks/feature-extraction)
- [All models under mit](https://savrn.com/models/licenses/mit)
- [Model comparisons](https://savrn.com/models/comparisons)
- [The model directory](https://savrn.com/models)
- [Open model prices by host](https://savrn.com/ai-index/pricing/open-models)

## Source

- Repository metadata, read 2026-10-19.
- [Beijing Academy of Artificial Intelligence website](https://github.com/FlagOpen/FlagEmbedding)
- [Hugging Face record](https://huggingface.co/BAAI/bge-base-en)
- [How the hub is built](https://savrn.com/model-hub/methodology)