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Gemma 3 12B vs Phi-4

Google
Gemma 3 12B

Google · 12B params · Quality: 71

Microsoft
Phi-4

Microsoft · 14.7B params · Quality: 83

Architecture Comparison

SpecGemma 3 12BPhi-4
TypeDENSEDENSE
Total Parameters12B14.7B
Active Parameters12B14.7B
Layers4840
Hidden Dimension3,0725,120
Attention Heads3240
KV Heads1610
Context Length131,07216,384
Precision (default)BF16BF16

Memory Requirements

PrecisionGemma 3 12BPhi-4
BF16 Weights24.0 GB29.4 GB
FP8 Weights12.0 GB14.7 GB
INT4 Weights6.0 GB7.3 GB
KV-Cache / Token393216 B204800 B
Activation Estimate1.00 GB1.50 GB

Minimum GPUs Needed (BF16)

H100 SXM1 GPU1 GPU
L40S1 GPU1 GPU

Quality Benchmarks

BenchmarkGemma 3 12BPhi-4
Overall7183
MMLU74.084.8
HumanEval44.067.0
GSM8K78.093.0
MT-Bench80.085.0

Gemma 3 12B

MMLU
74.0
HumanEval
44.0
GSM8K
78.0
MT-Bench
80.0

Phi-4

MMLU
84.8
HumanEval
67.0
GSM8K
93.0
MT-Bench
85.0

Capabilities

FeatureGemma 3 12BPhi-4
Tool Use✓ Yes✓ Yes
Vision✓ Yes✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✗ No✓ Yes
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes

API Pricing Comparison

Cheapest Output (Gemma 3 12B)

$0.10/M

Input: $0.05/M

Cheapest Output (Phi-4)

$0.14/M

Input: $0.07/M

ProviderGemma 3 12B In $/MOut $/MPhi-4 In $/MOut $/M
google$0.05$0.10
azure$0.07$0.14
together$0.15$0.15$0.20$0.20

Recommendation Summary

  • Phi-4 scores higher on overall quality (83 vs 71).
  • Gemma 3 12B is cheaper per output token ($0.10/M vs $0.14/M).
  • Gemma 3 12B has a smaller memory footprint (24.0 GB vs 29.4 GB BF16), making it easier to deploy on fewer GPUs.
  • Gemma 3 12B supports a longer context window (131,072 vs 16,384 tokens).
  • Phi-4 is stronger at code generation (HumanEval: 67.0 vs 44.0).
  • Phi-4 is better at math reasoning (GSM8K: 93.0 vs 78.0).

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