Phi-4 vs Llama 3.1 70B
Architecture Comparison
SpecPhi-4Llama 3.1 70B
TypeDENSEDENSE
Total Parameters14.7B70.6B
Active Parameters14.7B70.6B
Layers4080
Hidden Dimension5,1208,192
Attention Heads4064
KV Heads108
Context Length16,384131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionPhi-4Llama 3.1 70B
BF16 Weights29.4 GB141.2 GB
FP8 Weights14.7 GB70.6 GB
INT4 Weights7.3 GB35.3 GB
KV-Cache / Token204800 B327680 B
Activation Estimate1.50 GB2.50 GB
Minimum GPUs Needed (BF16)
H100 SXM1 GPU3 GPUs
L40S1 GPU4 GPUs
Quality Benchmarks
BenchmarkPhi-4Llama 3.1 70B
Overall8382
MMLU84.883.6
HumanEval67.058.5
GSM8K93.093.0
MT-Bench85.085.0
Phi-4
MMLU
84.8
HumanEval
67.0
GSM8K
93.0
MT-Bench
85.0
Llama 3.1 70B
MMLU
83.6
HumanEval
58.5
GSM8K
93.0
MT-Bench
85.0
Capabilities
FeaturePhi-4Llama 3.1 70B
Tool Use✓ Yes✓ Yes
Vision✗ No✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✓ Yes✗ No
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes
API Pricing Comparison
Cheapest Output (Phi-4)
$0.14/M
Input: $0.07/M
Cheapest Output (Llama 3.1 70B)
$0.79/M
Input: $0.59/M
| Provider | Phi-4 In $/M | Out $/M | Llama 3.1 70B In $/M | Out $/M |
|---|---|---|---|---|
| azure | $0.07 | $0.14 | — | — |
| together | $0.20 | $0.20 | $0.88 | $0.88 |
| groq | — | — | $0.59 | $0.79 |
| fireworks | — | — | $0.90 | $0.90 |
Recommendation Summary
- ‣Phi-4 scores higher on overall quality (83 vs 82).
- ‣Phi-4 is cheaper per output token ($0.14/M vs $0.79/M).
- ‣Phi-4 has a smaller memory footprint (29.4 GB vs 141.2 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Llama 3.1 70B supports a longer context window (131,072 vs 16,384 tokens).
- ‣Phi-4 is stronger at code generation (HumanEval: 67.0 vs 58.5).