Model
Model explorer

Phi-4-mini (3.8B)

OPEN
Microsoft · Phi-4 family · released Feb 26, 2025

Compact text-only Phi-4 (128K context) with built-in function calling and 22-language support; MIT-licensed, tops the 3-4B class.

ReasoningCodingVisionFunction callingTool useAgentic
529.8
Elo · rank #296
Parameters
3.8B
Active params
3.8B (dense)
Context
128K tokens
Architecture
Dense decoder-only Transformer with grouped-query attention
License
MIT
Languages
22+
API price (in/out)
$0.075 / $0.3
Modalities
text
Benchmark results
Bar shows position within the tracked field; marker = field best
ARC-ChallengeReasoning83.7%#34
best: Llama 3.1 405B · 96.9%
Arena-HardHuman preference32.8%#50
best: Qwen3-235B-A22B (Non-Thinking) · 96.1%
BIG-Bench HardReasoning70.4%#54
best: ERNIE 4.5 300B-A47B · 94.3%
BFCLAgents70.3%#22
best: SmolLM3 3B (No Thinking) · 92.3%
GPQA DiamondReasoning30.4%#261
best: GPT-5.6 · 94.6%
GSM8KMath88.6%#49
best: Llama 3.1 405B · 96.8%
HellaSwagReasoning69.1%#128
best: Claude 3 Opus · 95.4%
Humanity's Last ExamReasoning4.2%#125
best: Claude Sonnet 5 · 57.4%
HumanEval+Coding68.3%#20
best: Mistral Small 3.2 (24B) · 92.9%
HumanEvalCoding74.4%#66
best: Claude Opus 4.5 · 99.4%
IFEvalReasoning70.1%#113
best: Gemma 4 26B A4B · 98.5%
LiveCodeBenchCoding19.9%#163
best: DeepSeek-V4-Pro (Think Max) · 93.5%
MATH-500Math64.0%#105
best: GPT-5 · 99.4%
MBPP+Coding63.8%#23
best: Llama 3.1 405B · 88.6%
MBPPCoding65.3%#49
best: Llama-3.3-Nemotron-Super-49B v1 (Reasoning On) · 91.3%
MGSMMath63.9%#38
best: OpenAI o4-mini · 93.7%
MMLU-ProKnowledge52.8%#127
best: Claude Fable 5 · 91.5%
MMLUKnowledge67.3%#165
best: OpenAI o3 · 92.9%
MMMLUKnowledge49.3%#53
best: Gemini 3.1 Pro · 92.6%
PIQAReasoning77.6%#55
best: GPT-4o mini · 93.1%
Social IQaReasoning72.5%#9
best: Apple DCLM-Baseline 7B · 82.9%
TruthfulQAKnowledge66.4%#11
best: Phi-3.5-MoE (16x3.8B, 6.6B active) · 77.5%
WinoGrandeReasoning67.0%#112
best: PaLM 2 · 90.9%
Run it locally
VRAM @ Q4
3 GB
VRAM @ FP16
10 GB
Fits on (Q4)
RTX 3060 12GBRTX 4070 Ti 16GBRTX 3090 24GBRTX 4090 24GBRTX 5090 32GBM4 Pro 48GBM3 Max 128GBM3 Ultra 512GBA100 80GBH100 80GBH200 141GBB200 192GB
Throughput data unavailable.
Quantizations
GGUF · MLX · ONNX
API price $0.075/$0.3 · each benchmark row carries its own source badge (see methodology)