Updated minutes ago
Llama 2 70B
Meta · dense · 70B parameters · 4,096 context
Quality62.0
Architecture Details
TypeDENSE
Total Parameters70B
Active Parameters70B
Layers80
Hidden Dimension8,192
Attention Heads64
KV Heads64
Head Dimension128
Vocab Size32,000
Memory Requirements
BF16 Weights
140.0 GB
FP8 Weights
70.0 GB
INT4 Weights
35.0 GB
KV-Cache per Token2621440 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 INT4H100 PCIe INT4H100 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
H20optimal
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
478.0 tok/s
Cost/Month
$940
Cost/M Tokens
$0.75
GH200optimal
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
478.0 tok/s
Cost/Month
$2838
Cost/M Tokens
$2.26
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| together | $0.90 | $0.90 | Cheapest |
Quality Benchmarks
MMLU69.8
HumanEval30.0
GSM8K56.0
MT-Bench75.0
Capabilities
Features
✗ Tool Use✗ Vision✓ Code✗ Math✗ Reasoning✗ Multilingual✗ Structured Output
Supported Frameworks
vllmsglangtgitensorrt-llm
Supported Precisions
BF16 (default)FP8INT4