Whisper large-v2
dense 1.55B
Fields
id
models/whisper-large-v2Family
whisper
Vendor
OpenAI
Release year
2022
Architecture
dense
Params (B)
1.55
Active params (B)
1.55
Hidden size
1,280
Layers
32
KV heads
20
Head dim
64
GQA ratio
1
Max context
1,500
Context scaling method
native
Activation
gelu
Attention variant
MHA, encoder-decoder (cross-attention)
KV cache (bytes/token)
163,840
FLOPs per active token
3,100,000,000
Open weights
yes
License
apache-2.0
notes
ENCODER-DECODER. Same architecture as large-v3 except num_mel_bins 80 (vs 128 in large-v3). ENCODER: 32 layers, d_model 1280, 20 heads, encoder_ffn_dim 5120, gelu, num_mel_bins 80, max_source_positions 1500. DECODER: 32 layers, 20 heads, decoder_ffn_dim 5120, max_target_positions 448. KV CACHE: decoder self-attention 32 * 20 * 64 * 2 * 2 = 163,840 B/token = 160 KiB/token. Cross-attention over 1500 encoder frames: 32 * 20 * 64 * 1500 * 2 * 2 = 245,760,000 B = 234 MiB per in-flight request. STREAMING: not natively supported (offline/batch model).
task
speech-to-text
Notes
ENCODER-DECODER. Same architecture as large-v3 except num_mel_bins 80 (vs 128 in large-v3). ENCODER: 32 layers, d_model 1280, 20 heads, encoder_ffn_dim 5120, gelu, num_mel_bins 80, max_source_positions 1500. DECODER: 32 layers, 20 heads, decoder_ffn_dim 5120, max_target_positions 448. KV CACHE: decoder self-attention 32 * 20 * 64 * 2 * 2 = 163,840 B/token = 160 KiB/token. Cross-attention over 1500 encoder frames: 32 * 20 * 64 * 1500 * 2 * 2 = 245,760,000 B = 234 MiB per in-flight request. STREAMING: not natively supported (offline/batch model).
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