DeepSeek V3 vs Phi-4
Architecture Comparison
SpecDeepSeek V3Phi-4
TypeMOEDENSE
Total Parameters671B14.7B
Active Parameters37B14.7B
Layers6140
Hidden Dimension7,1685,120
Attention Heads12840
KV Heads110
Context Length131,07216,384
Precision (default)BF16BF16
Total Experts256N/A
Active Experts8N/A
Memory Requirements
PrecisionDeepSeek V3Phi-4
BF16 Weights1342.0 GB29.4 GB
FP8 Weights671.0 GB14.7 GB
INT4 Weights335.5 GB7.3 GB
KV-Cache / Token31232 B204800 B
Activation Estimate3.00 GB1.50 GB
Minimum GPUs Needed (BF16)
H100 SXMN/A1 GPU
L40SN/A1 GPU
Quality Benchmarks
BenchmarkDeepSeek V3Phi-4
Overall8683
MMLU87.184.8
HumanEval65.067.0
GSM8K89.393.0
MT-Bench87.085.0
DeepSeek V3
MMLU
87.1
HumanEval
65.0
GSM8K
89.3
MT-Bench
87.0
Phi-4
MMLU
84.8
HumanEval
67.0
GSM8K
93.0
MT-Bench
85.0
Capabilities
FeatureDeepSeek V3Phi-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 (DeepSeek V3)
$0.42/M
Input: $0.28/M
Cheapest Output (Phi-4)
$0.14/M
Input: $0.07/M
| Provider | DeepSeek V3 In $/M | Out $/M | Phi-4 In $/M | Out $/M |
|---|---|---|---|---|
| azure | — | — | $0.07 | $0.14 |
| together | $0.50 | $2.80 | $0.20 | $0.20 |
| deepseek | $0.28 | $0.42 | — | — |
Recommendation Summary
- ‣DeepSeek V3 scores higher on overall quality (86 vs 83).
- ‣Phi-4 is cheaper per output token ($0.14/M vs $0.42/M).
- ‣Phi-4 has a smaller memory footprint (29.4 GB vs 1342.0 GB BF16), making it easier to deploy on fewer GPUs.
- ‣DeepSeek V3 supports a longer context window (131,072 vs 16,384 tokens).
- ‣DeepSeek V3 uses MOE architecture while Phi-4 uses DENSE. MoE models activate fewer parameters per token, improving inference efficiency.
- ‣Phi-4 is stronger at code generation (HumanEval: 67.0 vs 65.0).
- ‣Phi-4 is better at math reasoning (GSM8K: 93.0 vs 89.3).