Microsoft/Dense

MicrosoftPhi-3.5 Mini 3.8B

Phi-3.5 Mini. Great balance of speed and intelligence for a sub-4B model.

chatcodingreasoningThinking
3.82B
Parameters
128K
Context length
9
Benchmarks
6
Quantizations
500K
HF downloads
Architecture
Dense
Released
2024-08-20
Layers
32
KV Heads
32
Head Dim
96
Family
phi

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.892.8 GBgood
Q5_K_S5.573.1 GBgood
Q5_K_M5.73.2 GBgood
Q6_K6.563.6 GBexcellent
Q8_08.54.5 GBlossless
FP16168.1 GBlossless

Select your GPU above to see speed estimates and compatibility for each quantization.

READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN PHI-3.5 MINI 3.8B NOW

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

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Benchmarks (9)

Arena Elo1435
IFEval69.0
HumanEval62.0
BBH62.0
MATH59.0
MMLU-PRO47.4
BigCodeBench36.8
GPQA30.5
MUSR6.4

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run phi3.5:3.8b-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA Tesla C2050
3 GB VRAM • 144 GB/s
NVIDIA
NVIDIA Tesla M2050
3 GB VRAM • 148 GB/s
NVIDIA
NVIDIA Tesla S2050
3 GB VRAM • 148 GB/s
NVIDIA

Find the best GPU for Phi-3.5 Mini 3.8B

Build Hardware for Phi-3.5 Mini 3.8B

Phi-3.5 Mini. Great balance of speed and intelligence for a sub-4B model.

▸ SPEC SHEET

Phi-3.5 Mini 3.8B3.82B Dense.

▸ SPECIFICATIONS
PARAMETERS
3.82B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
128K tokens
CAPABILITIES
chat, coding, reasoning
RELEASE DATE
2024-08-20
PROVIDER
Microsoft
FAMILY
phi
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.892.8 GB94%
Q5_K_S5.573.1 GB96%
Q5_K_M5.73.2 GB96%
Q6_K6.563.6 GB97%
Q8_08.54.5 GB100%
FP16168.1 GB100%
§ 01BENCHMARK SCORES
HumanEval62.0
MMLU-PRO47.4
MATH59.0
IFEval69.0
BBH62.0
GPQA30.5
MUSR6.4
BigCodeBench36.8
Arena Elo1435.0
§ 02RUN COMMAND

Run Phi-3.5 Mini 3.8B locally with Ollama — needs 2.8 GB VRAM at Q4_K_M:

$ollama run phi3.5:3.8b