Phi-4 vs Llama 3.1 405B
Architecture Comparison
SpecPhi-4Llama 3.1 405B
TypeDENSEDENSE
Total Parameters14.7B405B
Active Parameters14.7B405B
Layers40126
Hidden Dimension5,12016,384
Attention Heads40128
KV Heads108
Context Length16,384131,072
Precision (default)BF16BF16
Memory Requirements
PrecisionPhi-4Llama 3.1 405B
BF16 Weights29.4 GB810.0 GB
FP8 Weights14.7 GB405.0 GB
INT4 Weights7.3 GB202.5 GB
KV-Cache / Token204800 B516096 B
Activation Estimate1.50 GB5.00 GB
Minimum GPUs Needed (BF16)
H100 SXM1 GPUN/A
L40S1 GPUN/A
Quality Benchmarks
BenchmarkPhi-4Llama 3.1 405B
Overall8388
MMLU84.888.6
HumanEval67.061.0
GSM8K93.096.8
MT-Bench85.088.0
Phi-4
MMLU
84.8
HumanEval
67.0
GSM8K
93.0
MT-Bench
85.0
Llama 3.1 405B
MMLU
88.6
HumanEval
61.0
GSM8K
96.8
MT-Bench
88.0
Capabilities
FeaturePhi-4Llama 3.1 405B
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 405B)
$3.00/M
Input: $3.00/M
| Provider | Phi-4 In $/M | Out $/M | Llama 3.1 405B In $/M | Out $/M |
|---|---|---|---|---|
| azure | $0.07 | $0.14 | — | — |
| together | $0.20 | $0.20 | $3.50 | $3.50 |
| fireworks | — | — | $3.00 | $3.00 |
Recommendation Summary
- ‣Llama 3.1 405B scores higher on overall quality (88 vs 83).
- ‣Phi-4 is cheaper per output token ($0.14/M vs $3.00/M).
- ‣Phi-4 has a smaller memory footprint (29.4 GB vs 810.0 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Llama 3.1 405B supports a longer context window (131,072 vs 16,384 tokens).
- ‣Phi-4 is stronger at code generation (HumanEval: 67.0 vs 61.0).
- ‣Llama 3.1 405B is better at math reasoning (GSM8K: 96.8 vs 93.0).