Mixedbread mxbai-embed-large-v1
dense 0.335B
Fields
id
models/mxbai-embed-large-v1Family
mxbai
Vendor
Mixedbread AI
Release year
2024
Architecture
dense
Params (B)
0.335
Active params (B)
0.335
Hidden size
1,024
Layers
24
Max context
512
Context scaling method
native
Activation
gelu
Attention variant
bidirectional encoder (BERT), full attention, no causal mask
KV cache (bytes/token)
0
FLOPs per active token
670,000,000
Open weights
yes
License
Apache-2.0
embedding dims
1,024
notes
Encoder: kv_cache_bytes_per_token = 0, KV formula does not apply. Identical architecture to bge-large-en-v1.5, gte-large, and e5-large-v2: BERT-large, hidden 1024, 24 layers, 16 heads, intermediate 4096, vocab 30522, 512 max_position_embeddings. The Mixedbread model is distinguished by its training data and fine-tuning, not by architecture. Apache-2.0. GGUF and ONNX ports exist.
task
embedding
Notes
Encoder: kv_cache_bytes_per_token = 0, KV formula does not apply. Identical architecture to bge-large-en-v1.5, gte-large, and e5-large-v2: BERT-large, hidden 1024, 24 layers, 16 heads, intermediate 4096, vocab 30522, 512 max_position_embeddings. The Mixedbread model is distinguished by its training data and fine-tuning, not by architecture. Apache-2.0. GGUF and ONNX ports exist.
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