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Phi-4 vs Mistral Large 2

Microsoft
Phi-4

Microsoft · 14.7B params · Quality: 83

Mistral
Mistral Large 2

Mistral AI · 123B params · Quality: 82

Architecture Comparison

SpecPhi-4Mistral Large 2
TypeDENSEDENSE
Total Parameters14.7B123B
Active Parameters14.7B123B
Layers4088
Hidden Dimension5,12012,288
Attention Heads4096
KV Heads108
Context Length16,384131,072
Precision (default)BF16BF16

Memory Requirements

PrecisionPhi-4Mistral Large 2
BF16 Weights29.4 GB246.0 GB
FP8 Weights14.7 GB123.0 GB
INT4 Weights7.3 GB61.5 GB
KV-Cache / Token204800 B360448 B
Activation Estimate1.50 GB3.50 GB

Minimum GPUs Needed (BF16)

H100 SXM1 GPU4 GPUs
L40S1 GPU7 GPUs

Quality Benchmarks

BenchmarkPhi-4Mistral Large 2
Overall8382
MMLU84.884.0
HumanEval67.053.0
GSM8K93.091.2
MT-Bench85.084.0

Phi-4

MMLU
84.8
HumanEval
67.0
GSM8K
93.0
MT-Bench
85.0

Mistral Large 2

MMLU
84.0
HumanEval
53.0
GSM8K
91.2
MT-Bench
84.0

Capabilities

FeaturePhi-4Mistral Large 2
Tool Use✓ Yes✓ Yes
Vision✗ No✗ No
Code✓ Yes✓ Yes
Math✓ Yes✓ Yes
Reasoning✓ Yes✗ No
Multilingual✓ Yes✓ Yes
Structured Output✓ Yes✓ Yes

API Pricing Comparison

Cheapest Output (Phi-4)

$0.14/M

Input: $0.07/M

Cheapest Output (Mistral Large 2)

$2.50/M

Input: $2.50/M

ProviderPhi-4 In $/MOut $/MMistral Large 2 In $/MOut $/M
azure$0.07$0.14
together$0.20$0.20$2.50$2.50
mistral$2.00$6.00

Recommendation Summary

  • Phi-4 scores higher on overall quality (83 vs 82).
  • Phi-4 is cheaper per output token ($0.14/M vs $2.50/M).
  • Phi-4 has a smaller memory footprint (29.4 GB vs 246.0 GB BF16), making it easier to deploy on fewer GPUs.
  • Mistral Large 2 supports a longer context window (131,072 vs 16,384 tokens).
  • Phi-4 is stronger at code generation (HumanEval: 67.0 vs 53.0).
  • Phi-4 is better at math reasoning (GSM8K: 93.0 vs 91.2).

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