DeepSeek R1 vs Phi-4
Architecture Comparison
SpecDeepSeek R1Phi-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 R1Phi-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 R1Phi-4
Overall9283
MMLU90.884.8
HumanEval71.767.0
GSM8K97.393.0
MT-Bench89.085.0
DeepSeek R1
MMLU
90.8
HumanEval
71.7
GSM8K
97.3
MT-Bench
89.0
Phi-4
MMLU
84.8
HumanEval
67.0
GSM8K
93.0
MT-Bench
85.0
Capabilities
FeatureDeepSeek R1Phi-4
Tool Use✓ Yes✓ Yes
Vision✗ No✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✓ Yes✓ Yes
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes
API Pricing Comparison
Cheapest Output (DeepSeek R1)
$2.19/M
Input: $0.55/M
Cheapest Output (Phi-4)
$0.14/M
Input: $0.07/M
| Provider | DeepSeek R1 In $/M | Out $/M | Phi-4 In $/M | Out $/M |
|---|---|---|---|---|
| azure | — | — | $0.07 | $0.14 |
| together | $3.00 | $7.00 | $0.20 | $0.20 |
| deepseek | $0.55 | $2.19 | — | — |
Recommendation Summary
- ‣DeepSeek R1 scores higher on overall quality (92 vs 83).
- ‣Phi-4 is cheaper per output token ($0.14/M vs $2.19/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 R1 supports a longer context window (131,072 vs 16,384 tokens).
- ‣DeepSeek R1 uses MOE architecture while Phi-4 uses DENSE. MoE models activate fewer parameters per token, improving inference efficiency.
- ‣DeepSeek R1 is stronger at code generation (HumanEval: 71.7 vs 67.0).
- ‣DeepSeek R1 is better at math reasoning (GSM8K: 97.3 vs 93.0).