Llama 3.1 70B vs Llama 3.1 8B
Architecture Comparison
SpecLlama 3.1 70BLlama 3.1 8B
TypeDENSEDENSE
Total Parameters70.6B8.03B
Active Parameters70.6B8.03B
Layers8032
Hidden Dimension8,1924,096
Attention Heads6432
KV Heads88
Context Length131,072131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionLlama 3.1 70BLlama 3.1 8B
BF16 Weights141.2 GB16.1 GB
FP8 Weights70.6 GB8.0 GB
INT4 Weights35.3 GB4.0 GB
KV-Cache / Token327680 B131072 B
Activation Estimate2.50 GB1.00 GB
Minimum GPUs Needed (BF16)
H100 SXM3 GPUs1 GPU
L40S4 GPUs1 GPU
Quality Benchmarks
BenchmarkLlama 3.1 70BLlama 3.1 8B
Overall8265
MMLU83.669.4
HumanEval58.540.2
GSM8K93.079.6
MT-Bench85.078.0
Llama 3.1 70B
MMLU
83.6
HumanEval
58.5
GSM8K
93.0
MT-Bench
85.0
Llama 3.1 8B
MMLU
69.4
HumanEval
40.2
GSM8K
79.6
MT-Bench
78.0
Capabilities
FeatureLlama 3.1 70BLlama 3.1 8B
Tool Use✓ Yes✓ Yes
Vision✗ No✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✗ No✗ No
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes
API Pricing Comparison
Cheapest Output (Llama 3.1 70B)
$0.79/M
Input: $0.59/M
Cheapest Output (Llama 3.1 8B)
$0.08/M
Input: $0.05/M
| Provider | Llama 3.1 70B In $/M | Out $/M | Llama 3.1 8B In $/M | Out $/M |
|---|---|---|---|---|
| groq | $0.59 | $0.79 | $0.05 | $0.08 |
| together | $0.88 | $0.88 | $0.18 | $0.18 |
| fireworks | $0.90 | $0.90 | $0.20 | $0.20 |
Recommendation Summary
- ‣Llama 3.1 70B scores higher on overall quality (82 vs 65).
- ‣Llama 3.1 8B is cheaper per output token ($0.08/M vs $0.79/M).
- ‣Llama 3.1 8B has a smaller memory footprint (16.1 GB vs 141.2 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Llama 3.1 70B is stronger at code generation (HumanEval: 58.5 vs 40.2).
- ‣Llama 3.1 70B is better at math reasoning (GSM8K: 93.0 vs 79.6).