# bge-large-en-v1.5 by Beijing Academy of Artificial Intelligence
Source: https://savrn.com/models/bge-large-en-v1-5
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

---

## Runs On

What it takes to serve bge-large-en-v1.5 (335M 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 | 0.7 GB | 0.8 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 | 0.3 GB | 0.4 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 | 0.2 GB | 0.2 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 23, 2026.

[bge-large-en-v1.5 on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/bge-large-en-v1-5/gpus)

## SAVRN's Notes on bge-large-en-v1.5

335M parameters across 24 layers and a hidden size of 1,024 still total 0.8 GB at 16-bit, 0.2 GB at 4-bit, with the same 512-token context as its smaller siblings. One 192 GB MI300X at $1.85 an hour remains the cheapest setup we price, and it is idle regardless. Downloads of 9.8M a month trail small's 63.4M and base's 10.4M — the market mostly votes smaller or newer, so buy this only when its scores pay on your corpus.

MIT is about as short as licenses get: commercial use, modification, redistribution, notices kept. The 4.0 GB checkpoint is float32, five times the 16-bit footprint, stored as bin, ONNX and safetensors copies across 14 files. The MTEB figures on the page were obtained with MTEB v2.10.12, so check evaluator versions before comparing against neighbors. Nothing has changed since 2024-02-21, and the publisher steers long-context users toward bge-m3 and its 8,192-token input.

SAVRN Research

## Model Card

By Beijing Academy of Artificial Intelligence, published under mit, revision d4aa6901d3a4.

### FlagEmbedding

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

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

If you are looking for a model that supports more languages, longer texts, and other retrieval methods, you can try using [bge-m3](https://savrn.com/models/bge-m3).

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

FlagEmbedding focuses on retrieval-augmented LLMs, consisting of the following projects currently:

- Long-Context LLM: [Activation Beacon](https://github.com/FlagOpen/FlagEmbedding/tree/master/Long_LLM/activation_beacon)
- Fine-tuning of LM : [LM-Cocktail](https://github.com/FlagOpen/FlagEmbedding/tree/master/LM_Cocktail)
- Dense Retrieval: [BGE-M3](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/BGE_M3), [LLM Embedder](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/llm_embedder), [BGE Embedding](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/baai_general_embedding)
- Reranker Model: [BGE Reranker](https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/reranker)
- Benchmark: [C-MTEB](https://github.com/FlagOpen/FlagEmbedding/tree/master/C_MTEB)

### News

[Read the full model card (2,707 words)](https://savrn.com/models/bge-large-en-v1-5/card)

## Configuration

Architecture

BertModel

Context length (tokens)

512

Layers

24

Hidden size

1,024

Feed-forward size

4,096

Attention heads

16

Vocabulary size

30,522

Stored precision

float32

Model type

bert

## Identity and Version

Repository

BAAI/bge-large-en-v1.5

Publisher

Beijing Academy of Artificial Intelligence

Task

Feature extraction

Modality

Text

Library

sentence-transformers

Parameters

335M parameters

Languages

en

Revision

d4aa6901d3a41ba39fb536a557fa166f842b0e09

First published

2023-09-12

Last updated

2024-02-21

## Files and Weights

14 files, 4.0 GB in total. The weights are 3 files totalling 4.0 GB in bin, onnx, safetensors.

Weights3 files · 4.0 GB

Configuration6 files · 1.6 KB

Tokenizer3 files · 943.3 KB

Documentation1 file · 94.6 KB

Repository1 file · 1.5 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| model.safetensors | Weights | 1.3 GB | 45e1954914e2 |
| onnx/model.onnx | Weights | 1.3 GB | 69ed3f810d3b |
| pytorch_model.bin | Weights | 1.3 GB | 51e14ed95fb8 |
| 1_Pooling/config.json | Configuration | 191 B | — |
| config.json | Configuration | 779 B | — |
| config_sentence_transformers.json | Configuration | 124 B | — |
| modules.json | Configuration | 349 B | — |
| sentence_bert_config.json | Configuration | 52 B | — |
| special_tokens_map.json | Configuration | 125 B | — |
| README.md | Documentation | 94.6 KB | — |
| .gitattributes | Repository | 1.5 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

4.0 GB

[Download from Beijing Academy of Artificial Intelligence](https://huggingface.co/BAAI/bge-large-en-v1.5)

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)
- Described by [arXiv:2311.13534](https://savrn.com/papers/lm-cocktail-resilient-tuning-of-language-models-via-model-merging)
- Described by [arXiv:2312.15503](https://savrn.com/papers/making-large-language-models-a-better-foundation-for-dense-retrieval)
- Described by [arXiv:2401.03462](https://savrn.com/papers/soaring-from-4k-to-400k-extending-llm-s-context-with-activation-beacon)

## 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/BRIGHT | Task BrightAopsRetrievalMetric BrightAopsRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 6 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightAopsRetrieval_default_standardMetric BrightAopsRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 6 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightBiologyLongRetrievalMetric BrightBiologyLongRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 16.424 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightBiologyLongRetrieval_default_longMetric BrightBiologyLongRetrieval_default_longSetup Obtained using MTEB v2.10.12Comparison conditions not established | 16.424 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightBiologyRetrievalMetric BrightBiologyRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 11.67 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightBiologyRetrieval_default_standardMetric BrightBiologyRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 11.67 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightEarthScienceLongRetrievalMetric BrightEarthScienceLongRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 27.73 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightEarthScienceLongRetrieval_default_longMetric BrightEarthScienceLongRetrieval_default_longSetup Obtained using MTEB v2.10.12Comparison conditions not established | 27.73 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightEarthScienceRetrievalMetric BrightEarthScienceRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 24.558 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightEarthScienceRetrieval_default_standardMetric BrightEarthScienceRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 24.558 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightEconomicsLongRetrievalMetric BrightEconomicsLongRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 20.874 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightEconomicsLongRetrieval_default_longMetric BrightEconomicsLongRetrieval_default_longSetup Obtained using MTEB v2.10.12Comparison conditions not established | 20.874 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightEconomicsRetrievalMetric BrightEconomicsRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 16.605 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightEconomicsRetrieval_default_standardMetric BrightEconomicsRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 16.605 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightLeetcodeRetrievalMetric BrightLeetcodeRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 26.681 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightLeetcodeRetrieval_default_standardMetric BrightLeetcodeRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 26.681 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightPonyLongRetrievalMetric BrightPonyLongRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 0.36 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightPonyLongRetrieval_default_longMetric BrightPonyLongRetrieval_default_longSetup Obtained using MTEB v2.10.12Comparison conditions not established | 0.36 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightPonyRetrievalMetric BrightPonyRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 5.724 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightPonyRetrieval_default_standardMetric BrightPonyRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 5.724 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightPsychologyLongRetrievalMetric BrightPsychologyLongRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 11.584 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightPsychologyLongRetrieval_default_longMetric BrightPsychologyLongRetrieval_default_longSetup Obtained using MTEB v2.10.12Comparison conditions not established | 11.584 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightPsychologyRetrievalMetric BrightPsychologyRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 17.464 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightPsychologyRetrieval_default_standardMetric BrightPsychologyRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 17.464 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightRoboticsLongRetrievalMetric BrightRoboticsLongRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 10.891 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightRoboticsLongRetrieval_default_longMetric BrightRoboticsLongRetrieval_default_longSetup Obtained using MTEB v2.10.12Comparison conditions not established | 10.891 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightRoboticsRetrievalMetric BrightRoboticsRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 11.713 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightRoboticsRetrieval_default_standardMetric BrightRoboticsRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 11.713 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightStackoverflowLongRetrievalMetric BrightStackoverflowLongRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 13.248 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightStackoverflowLongRetrieval_default_longMetric BrightStackoverflowLongRetrieval_default_longSetup Obtained using MTEB v2.10.12Comparison conditions not established | 13.248 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightStackoverflowRetrievalMetric BrightStackoverflowRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 10.83 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightStackoverflowRetrieval_default_standardMetric BrightStackoverflowRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 10.83 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightSustainableLivingLongRetrievalMetric BrightSustainableLivingLongRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 16.898 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightSustainableLivingLongRetrieval_default_longMetric BrightSustainableLivingLongRetrieval_default_longSetup Obtained using MTEB v2.10.12Comparison conditions not established | 16.898 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightSustainableLivingRetrievalMetric BrightSustainableLivingRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 13.326 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightSustainableLivingRetrieval_default_standardMetric BrightSustainableLivingRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 13.326 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightTheoremQAQuestionsRetrievalMetric BrightTheoremQAQuestionsRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 13.004 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightTheoremQAQuestionsRetrieval_default_standardMetric BrightTheoremQAQuestionsRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 13.004 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightTheoremQATheoremsRetrievalMetric BrightTheoremQATheoremsRetrievalSetup Obtained using MTEB v2.10.12Comparison conditions not established | 6.9 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |
| mteb/BRIGHT | Task BrightTheoremQATheoremsRetrieval_default_standardMetric BrightTheoremQATheoremsRetrieval_default_standardSetup Obtained using MTEB v2.10.12Comparison conditions not established | 6.9 | [Obtained using MTEB v2.10.12](https://github.com/embeddings-benchmark/mteb/) Reported by a third party | Evaluated revision not stated | 2026-03-26 |

## Memory Requirements

| Precision | Weights in memory |
| --- | --- |
| As published | 4.0 GB |
| 16-bit | 0.7 GB |
| 8-bit | 0.3 GB |
| 4-bit | 0.2 GB |

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

## Built on This Model

- Derived from[KielEmbed-Pro](https://savrn.com/models/kielembed-pro)

## Compare bge-large-en-v1.5

- [bge-large-en-v1.5 vs multilingual-e5-large-instruct](https://savrn.com/models/compare/bge-large-en-v1-5-vs-multilingual-e5-large-instruct)
- [bge-large-en-v1.5 vs mxbai-embed-large-v1](https://savrn.com/models/compare/bge-large-en-v1-5-vs-mxbai-embed-large-v1)
- [bge-large-en-v1.5 vs UAE-Large-V1](https://savrn.com/models/compare/bge-large-en-v1-5-vs-uae-large-v1)

## Questions About bge-large-en-v1.5

### How much GPU memory does bge-large-en-v1.5 need?

About 0.8 GB at 16-bit and 0.2 GB at 4-bit: the weights (335M parameters) plus a working margin. A long context needs more.

### What is the cheapest GPU to run bge-large-en-v1.5 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-large-en-v1.5 commercially?

Yes. bge-large-en-v1.5 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-large-en-v1.5's context length?

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

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### [Vela-1.0-Omni-Nano](https://savrn.com/models/vela-1-0-omni-nano)

[vLLM Semantic Router](https://savrn.com/model-publishers/llm-semantic-router)

Text, images, speech and environmental audio in one embedding space. Vela Omni Nano supports multimodal search, routing and clustering with normalized vectors that can be compared directly. A frozen CLAP audio branch adds environmental-sound information to the existing speech representation. Text and image computations are retained; audio embeddings are newly trained and evaluated. Architecture and measured identity. Scores are 0–100; higher is better. The comparison uses the same held-out evaluation examples, complete retrieval pools and 128-token text cap for both models. Bold marks improvement over the original small model. These known test pools are reused across releases. The common…

Open weights apache-2.0 164M parameters pytorch

[View model](https://savrn.com/models/vela-1-0-omni-nano)

Model · Feature extraction

### [jina-embeddings-v2-base-code](https://savrn.com/models/jina-embeddings-v2-base-code)

[Jina AI](https://savrn.com/model-publishers/jinaai)

The easiest way to starting using jina-embeddings-v2-base-code is to use Jina AI's Embedding API. jina-embeddings-v2-base-code is an multilingual embedding model speaks English and 30 widely used programming languages. Same as other jina-embeddings-v2 series, it supports 8192 sequence length. jina-embeddings-v2-base-code is based on a Bert architecture (JinaBert) that supports the symmetric bidirectional variant of ALiBi to allow longer sequence length. The backbone jina-bert-v2-base-code is pretrained on the github-code dataset. The model is further trained on Jina AI's collection of more than 150 millions of coding question answer and docstring source code pairs. These pairs were obtained…

Open weights apache-2.0 161M parameters 8,192 tokens sentence-transformers

[View model](https://savrn.com/models/jina-embeddings-v2-base-code)

## Beijing Academy of Artificial Intelligence

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## Versions

- [d4aa6901d3a4](https://savrn.com/models/bge-large-en-v1-5/versions/d4aa6901d3a4) · current 2026-10-23

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## Source

- Repository metadata, read 2026-10-19.
- [Beijing Academy of Artificial Intelligence website](https://github.com/FlagOpen/FlagEmbedding)
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