bge-base-en-v1.5-course-recommender-v5 vs LLM2Vec-Meta-Llama-3-8B-Instruct-mntp
Specs, VRAM requirements and download trends — updated 8 November 2026.
datasocietyco · A · Open weights
Params
110 M
Context
512
30d
2.9 M
McGill-NLP · B · Open weights
Params
8.0 B
Context
8,192
30d
396 K
mit · commercial OK
Specification comparison
Differences are highlighted; identical values are muted.
| Specification | bge-base-en-v1.5-course-recommender-v5 | LLM2Vec-Meta-Llama-3-8B-Instruct-mntp |
|---|---|---|
| Parameters | 110 M | 8.0 B |
| Architecture | BertModel | LlamaEncoderModel |
| Context length | 512 | 8,192 |
| Licence | — | mit |
| Commercial use | Unknown | Allowed |
| Languages | — | 1 |
| Downloads 30d | 2,895,119 | 396,165 |
| Downloads all time | 19.1 M | 2.4 M |
| Quantizations on the Hub | SAFETENSORS | SAFETENSORS |
| Gated | No | No |
| First seen on the Hub | 2025-01-09 | 2024-04-30 |
Download trend
Daily snapshots, last 90 days (13 Aug – 10 Nov)
4.3 M377 K
bge-base-en-v1.5-course-recommender-v5
LLM2Vec-Meta-Llama-3-8B-Instruct-mntp
VRAM side by side
On RTX 4090 · 24 GB · 8K context unless noted
bge-base-en-v1.5-course-recommender-v5 · fp16
1.0 GB / 24 GB
LLM2Vec-Meta-Llama-3-8B-Instruct-mntp · fp16
1.9 GB / 24 GB
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