FitMyLLM
Mistral AI/Dense

Mistral AIMinistral 3 3B

Ministral 3 3B — Mistral's small dense instruct model with a 256K context, aimed at edge and on-device deployment.

chatcodingmultilingualtool_use
3.85B
Parameters
256K
Context length
12
Benchmarks
6
Quantizations
392K
HF downloads
Architecture
Dense
Released
2025-12-02
Layers
26
KV Heads
8
Head Dim
128
Family
mistral

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q4_K_M4.89
4.1 GB
2.8 + 1.2 KV
good
Q5_K_S5.57
4.4 GB
3.2 + 1.2 KV
good
Q5_K_M5.7
4.5 GB
3.2 + 1.2 KV
good
Q6_K6.56
4.9 GB
3.6 + 1.2 KV
excellent
Q8_08.5
5.8 GB
4.6 + 1.2 KV
lossless
FP1616
9.4 GB
8.2 + 1.2 KV
lossless

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

Deploying for a team or in production? Size GPUs, cost & scaling in Enterprise →
READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN MINISTRAL 3 3B NOW

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

Community Ratings

Loading ratings...

Benchmarks (12)

MMLU-PRO52.4
GPQA Diamond35.8
IFBench26.8
τ²-Bench24.9
LiveCodeBench24.7
AIME22.0
AA Math22.0
AA Long Context16.0
SciCode14.4
AA Intelligence7.1
HLE5.4
AA Coding4.8

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run ministral-3:3b-instruct-2512-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 Ministral 3 3B

Build Hardware for Ministral 3 3B
▸ SPEC SHEET

Ministral 3 3B3.85B Dense.

▸ SPECIFICATIONS
PARAMETERS
3.85B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, coding, multilingual, tool_use
RELEASE DATE
2025-12-02
PROVIDER
Mistral AI
FAMILY
mistral
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.892.8 GB94%
Q5_K_S5.573.2 GB96%
Q5_K_M5.73.2 GB96%
Q6_K6.563.6 GB97%
Q8_08.54.6 GB100%
FP16168.2 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO52.4
GPQA Diamond35.8
LiveCodeBench24.7
AIME22.0
HLE5.4
AA Intelligence7.1
AA Coding4.8
AA Math22.0
aa_ifbench26.8
aa_tau224.9
aa_scicode14.4
aa_lcr16.0
§ 02RUN COMMAND

Run Ministral 3 3B locally with Ollama — needs 2.8 GB VRAM at Q4_K_M:

$ollama run ministral-3:3b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M