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Embedding

Cohere Embed English v3

Cohere · dense · 0.5B parameters · 512 context

Quality
50.0

Architecture Details

TypeDENSE
Total Parameters0.5B
Active Parameters0.5B
Layers24
Hidden Dimension1,024
Attention Heads16
KV Heads16
Head Dimension64
Vocab Size256,000

Memory Requirements

BF16 Weights

1.0 GB

FP8 Weights

0.5 GB

INT4 Weights

0.3 GB

KV-Cache per Token49152 bytes
Activation Estimate0.10 GB

Fits on (single-node)

B200 SXM BF16B100 SXM BF16GB200 NVL72 (per GPU) BF16GB300 NVL72 (per GPU) BF16H200 SXM BF16H100 SXM BF16H100 PCIe BF16H100 NVL BF16

GPU Recommendations

B200 SXMgood

BF16 · 1 GPU · tensorrt-llm

78/100

score

Throughput

3.5K tok/s

Cost/Month

$4261

Cost/M Tokens

$0.46

Use this config →
B100 SXMgood

BF16 · 1 GPU · tensorrt-llm

78/100

score

Throughput

3.5K tok/s

Cost/Month

$4271

Cost/M Tokens

$0.46

Use this config →
GB200 NVL72 (per GPU)good

BF16 · 1 GPU · tensorrt-llm

78/100

score

Throughput

3.5K tok/s

Cost/Month

$6169

Cost/M Tokens

$0.67

Use this config →

API Pricing Comparison

ProviderInput $/MOutput $/MBadges
cohere$0.10$0.10
Cheapest

Capabilities

Features

Tool Use Vision Code Math Reasoning Multilingual Structured Output

Supported Frameworks

Supported Precisions

BF16 (default)

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