Llama 3.3 70B vs Phi-4
Architecture Comparison
SpecLlama 3.3 70BPhi-4
TypeDENSEDENSE
Total Parameters70.6B14.7B
Active Parameters70.6B14.7B
Layers8040
Hidden Dimension8,1925,120
Attention Heads6440
KV Heads810
Context Length131,07216,384
Precision (default)BF16BF16
Memory Requirements
PrecisionLlama 3.3 70BPhi-4
BF16 Weights141.2 GB29.4 GB
FP8 Weights70.6 GB14.7 GB
INT4 Weights35.3 GB7.3 GB
KV-Cache / Token327680 B204800 B
Activation Estimate2.50 GB1.50 GB
Minimum GPUs Needed (BF16)
H100 SXM3 GPUs1 GPU
L40S4 GPUs1 GPU
Quality Benchmarks
BenchmarkLlama 3.3 70BPhi-4
Overall8483
MMLU86.084.8
HumanEval60.067.0
GSM8K94.093.0
MT-Bench86.085.0
Llama 3.3 70B
MMLU
86.0
HumanEval
60.0
GSM8K
94.0
MT-Bench
86.0
Phi-4
MMLU
84.8
HumanEval
67.0
GSM8K
93.0
MT-Bench
85.0
Capabilities
FeatureLlama 3.3 70BPhi-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 3.3 70B)
$0.79/M
Input: $0.59/M
Cheapest Output (Phi-4)
$0.14/M
Input: $0.07/M
| Provider | Llama 3.3 70B In $/M | Out $/M | Phi-4 In $/M | Out $/M |
|---|---|---|---|---|
| azure | — | — | $0.07 | $0.14 |
| together | $0.88 | $0.88 | $0.20 | $0.20 |
| groq | $0.59 | $0.79 | — | — |
| fireworks | $0.90 | $0.90 | — | — |
Recommendation Summary
- ‣Llama 3.3 70B scores higher on overall quality (84 vs 83).
- ‣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 3.3 70B supports a longer context window (131,072 vs 16,384 tokens).
- ‣Phi-4 is stronger at code generation (HumanEval: 67.0 vs 60.0).
- ‣Llama 3.3 70B is better at math reasoning (GSM8K: 94.0 vs 93.0).