Phi-4 Mini (Unsloth)

3.8B dense parameters, synthetic training data, and a pronounced reasoning specialization: Phi-4-mini is Microsoft’s compact model for math, logic, and structured output. MIT license, 128,000 tokens of context, locally deployable as an Unsloth GGUF — not a broad generalist, but a specialist at Nano scale.

Microsoft Version 4 Commercial use permitted Dense 3.8 B (3.8 B active) 128 K Context 06/2024 locally tested

  • Open Weights
  • Nano
  • llama.cpp
  • Text
  • Instruction-Tuned
  • Real-Time

Sovereign Risk: LOW TODO

Key metrics

Score · Latency · Cost · Quality

Total Score Bronze
58.41
Routine
34.53
Reasoning
23.88

Rank #95

LLM Judge Avg
2.79
100 Coverage
Avg Task Duration
17.44
Real-Time
Token Rate
46.13
Output Rate
P95 Latency
20.51
Top 5 %
Total Tokens
62900
Output Volume
Cost per 1K
$0
USD / 1K Requests
Benchmark Cost
$0
Total · 62900 tok

Benchmark modules

10 modules · weighted · vs. model median & top performer

Phi-4 Mini (Unsloth) Best model Ø All models
Code Quality 56.7
CLI Benchmark 78.89
Logical Reasoning 61.09
UX Writing 57.75
Documentation 50.85
Content Transform. 53.71
Cultural Intelligence 52.3
Synthesis Quality 47.5
Tool Execution 88.33
ToolUse Score 66.25
Benchmark Cost $0

Token efficiency & latency

Consumption per module vs. model median

Token consumption per module

Performance profile