Llama 3.1 8B vs Phi-4
Architecture Comparison
SpecLlama 3.1 8BPhi-4
TypeDENSEDENSE
Total Parameters8.03B14.7B
Active Parameters8.03B14.7B
Layers3240
Hidden Dimension4,0965,120
Attention Heads3240
KV Heads810
Context Length131,07216,384
Precision (default)BF16BF16
Memory Requirements
PrecisionLlama 3.1 8BPhi-4
BF16 Weights16.1 GB29.4 GB
FP8 Weights8.0 GB14.7 GB
INT4 Weights4.0 GB7.3 GB
KV-Cache / Token131072 B204800 B
Activation Estimate1.00 GB1.50 GB
Minimum GPUs Needed (BF16)
H100 SXM1 GPU1 GPU
L40S1 GPU1 GPU
Quality Benchmarks
BenchmarkLlama 3.1 8BPhi-4
Overall6583
MMLU69.484.8
HumanEval40.267.0
GSM8K79.693.0
MT-Bench78.085.0
Llama 3.1 8B
MMLU
69.4
HumanEval
40.2
GSM8K
79.6
MT-Bench
78.0
Phi-4
MMLU
84.8
HumanEval
67.0
GSM8K
93.0
MT-Bench
85.0
Capabilities
FeatureLlama 3.1 8BPhi-4
Tool Use✓ Yes✓ Yes
Vision✗ No✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✗ No✓ Yes
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes
API Pricing Comparison
Cheapest Output (Llama 3.1 8B)
$0.08/M
Input: $0.05/M
Cheapest Output (Phi-4)
$0.14/M
Input: $0.07/M
| Provider | Llama 3.1 8B In $/M | Out $/M | Phi-4 In $/M | Out $/M |
|---|---|---|---|---|
| groq | $0.05 | $0.08 | — | — |
| azure | — | — | $0.07 | $0.14 |
| together | $0.18 | $0.18 | $0.20 | $0.20 |
| fireworks | $0.20 | $0.20 | — | — |
Recommendation Summary
- ‣Phi-4 scores higher on overall quality (83 vs 65).
- ‣Llama 3.1 8B is cheaper per output token ($0.08/M vs $0.14/M).
- ‣Llama 3.1 8B has a smaller memory footprint (16.1 GB vs 29.4 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Llama 3.1 8B supports a longer context window (131,072 vs 16,384 tokens).
- ‣Phi-4 is stronger at code generation (HumanEval: 67.0 vs 40.2).
- ‣Phi-4 is better at math reasoning (GSM8K: 93.0 vs 79.6).