gte-large-en-v1.5
We introduce gte-v1.5 series, upgraded gte embeddings that support the context length of up to 8192, while further enhancing model performance. The models are built upon the transformer++ encoder backbone (BERT + RoPE + GLU).
Params
430 M
Context
8,192
Downloads 30d
1.9 M
Likes
254
Download history
daily snapshots · 106 days
▲ 596 K in the last 30 days (44.6%)
2.1 M1.4 M
Oct 12Oct 22Nov 1Nov 10
2.1 M872 K
Aug 13Sep 12Oct 12Nov 10
2.1 M872 K
Jul 28Sep 1Oct 6Nov 10
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 1.7 GB | 2.5 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- NewModel
- Parameters
- 430 M
- Tensor type
- F32
- Context length
- 8,192
- Vocabulary
- 30,528
- Layers / heads
- 24 / 16
- Licence
- apache-2.0
- First seen on the Hub
- 2024-04-20
- Training datasets
- allenai/c4
- MTEB ArguAna (reported)
- 87.98
- MTEB BIOSSES (reported)
- 85.117602112908
- MTEB ArxivClusteringP2P (reported)
- 48.467787861077
- MTEB ArxivClusteringS2S (reported)
- 43.391983919143
- MTEB BiorxivClusteringP2P (reported)
- 40.577932830194
- MTEB BiorxivClusteringS2S (reported)
- 37.944256238651
- MTEB AskUbuntuDupQuestions (reported)
- 75.933144264169
- MTEB Banking77Classification (reported)
- 87.291329459996
- MTEB CQADupstackAndroidRetrieval (reported)
- 32.978
- MTEB AmazonPolarityClassification (reported)
- 93.958481377169
- MTEB AmazonReviewsClassification (en) (reported)
- 53.801223340128
- MTEB AmazonCounterfactualClassification (en) (reported)
- 66.712703108839
- Added to our catalog
- 2026-07-28
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