Mixtral 8x22B vs Phi-4
Architecture Comparison
SpecMixtral 8x22BPhi-4
TypeMOEDENSE
Total Parameters141B14.7B
Active Parameters39B14.7B
Layers5640
Hidden Dimension6,1445,120
Attention Heads4840
KV Heads810
Context Length65,53616,384
Precision (default)BF16BF16
Total Experts8N/A
Active Experts2N/A
Memory Requirements
PrecisionMixtral 8x22BPhi-4
BF16 Weights282.0 GB29.4 GB
FP8 Weights141.0 GB14.7 GB
INT4 Weights70.5 GB7.3 GB
KV-Cache / Token229376 B204800 B
Activation Estimate2.50 GB1.50 GB
Minimum GPUs Needed (BF16)
H100 SXM5 GPUs1 GPU
L40S7 GPUs1 GPU
Quality Benchmarks
BenchmarkMixtral 8x22BPhi-4
Overall7383
MMLU77.884.8
HumanEval46.067.0
GSM8K78.493.0
MT-Bench80.085.0
Mixtral 8x22B
MMLU
77.8
HumanEval
46.0
GSM8K
78.4
MT-Bench
80.0
Phi-4
MMLU
84.8
HumanEval
67.0
GSM8K
93.0
MT-Bench
85.0
Capabilities
FeatureMixtral 8x22BPhi-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 (Mixtral 8x22B)
$1.20/M
Input: $1.20/M
Cheapest Output (Phi-4)
$0.14/M
Input: $0.07/M
| Provider | Mixtral 8x22B In $/M | Out $/M | Phi-4 In $/M | Out $/M |
|---|---|---|---|---|
| azure | — | — | $0.07 | $0.14 |
| together | $1.20 | $1.20 | $0.20 | $0.20 |
| mistral | $2.00 | $6.00 | — | — |
Recommendation Summary
- ‣Phi-4 scores higher on overall quality (83 vs 73).
- ‣Phi-4 is cheaper per output token ($0.14/M vs $1.20/M).
- ‣Phi-4 has a smaller memory footprint (29.4 GB vs 282.0 GB BF16), making it easier to deploy on fewer GPUs.
- ‣Mixtral 8x22B supports a longer context window (65,536 vs 16,384 tokens).
- ‣Mixtral 8x22B 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 46.0).
- ‣Phi-4 is better at math reasoning (GSM8K: 93.0 vs 78.4).