Updated minutes ago
DeepSeek LLM 67B
DeepSeek · dense · 67B parameters · 4,096 context
Quality66.0
Architecture Details
TypeDENSE
Total Parameters67B
Active Parameters67B
Layers95
Hidden Dimension8,192
Attention Heads64
KV Heads8
Head Dimension128
Vocab Size102,400
Memory Requirements
BF16 Weights
134.0 GB
FP8 Weights
67.0 GB
INT4 Weights
33.5 GB
KV-Cache per Token655360 bytes
Activation Estimate2.50 GB
Fits on (single-node)
B200 SXM BF16B100 SXM BF16GB200 NVL72 (per GPU) BF16GB300 NVL72 (per GPU) BF16H200 SXM FP8H100 SXM FP8H100 PCIe FP8H100 NVL FP8
GPU Recommendations
H200 SXMoptimal
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
560.0 tok/s
Cost/Month
$2553
Cost/M Tokens
$1.73
H100 NVLoptimal
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
491.7 tok/s
Cost/Month
$2932
Cost/M Tokens
$2.27
H20optimal
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
499.4 tok/s
Cost/Month
$940
Cost/M Tokens
$0.72
API Pricing Comparison
No API pricing data available for this model.
Quality Benchmarks
MMLU71.3
HumanEval42.0
GSM8K72.0
MT-Bench76.0
Capabilities
Features
✗ Tool Use✗ Vision✓ Code✓ Math✗ Reasoning✓ Multilingual✗ Structured Output
Supported Frameworks
vllmsglangtgitensorrt-llm
Supported Precisions
BF16 (default)FP8INT4