FitMyLLM
Mistral AI/Dense

Mistral AIMagistral Small 24B

Mistral's first dedicated reasoning model. Chain-of-thought reasoning under Apache 2.0.

chatreasoningcoding
24B
Parameters
128K
Context length
10
Benchmarks
10
Quantizations
Architecture
Dense
Released
2025-06-01
Layers
40
KV Heads
8
Head Dim
128
Family
mistral

Quantization Options

QuantBitsVRAMQuality
Q3_K_M412.5 GBlow
Q3_K_L4.313.4 GBmoderate
IQ4_XS4.4613.9 GBmoderate
Q4_K_S4.6714.5 GBmoderate
Q4_K_M4.8915.2 GBgood
Q5_K_S5.5717.2 GBgood
Q5_K_M5.717.6 GBgood
Q6_K6.5620.2 GBexcellent
Q8_08.526.0 GBlossless
FP161648.5 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 MAGISTRAL SMALL 24B NOW

Rent on RunPod →Or Vast.ai →

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

Community Ratings

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Benchmarks (10)

AIME70.7
GPQA Diamond68.2
IFEval65.7
LiveCodeBench55.8
BBH52.8
MMLU-PRO49.4
BigCodeBench36.1
MATH35.6
GPQA18.6
MUSR17.1

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run magistral:24b-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
HuggingFaceOllama LibraryGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA RTX 5080
16 GB VRAM • 960 GB/s
NVIDIA
$999
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 5070 Ti
16 GB VRAM • 896 GB/s
NVIDIA
$749
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4080 SUPER
16 GB VRAM • 736 GB/s
NVIDIA
$999
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4080
16 GB VRAM • 717 GB/s
NVIDIA
$1199
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4070 Ti SUPER
16 GB VRAM • 672 GB/s
NVIDIA
$799
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4060 Ti 16GB
16 GB VRAM • 288 GB/s
NVIDIA
$499
AmazonNeweggeBayPCPartPicker
AMD RX 7900 GRE
16 GB VRAM • 576 GB/s
AMD
$549
AmazonNeweggeBayPCPartPicker
AMD RX 7800 XT
16 GB VRAM • 624 GB/s
AMD
$499
AmazonNeweggeBayPCPartPicker
AMD RX 7600 XT
16 GB VRAM • 288 GB/s
AMD
$329
AmazonNeweggeBayPCPartPicker
AMD RX 6950 XT
16 GB VRAM • 576 GB/s
AMD
$449
AmazonNeweggeBayPCPartPicker
AMD RX 6900 XT
16 GB VRAM • 512 GB/s
AMD
$469
AmazonNeweggeBayPCPartPicker
AMD RX 6800 XT
16 GB VRAM • 512 GB/s
AMD
$599
AmazonNeweggeBayPCPartPicker
AMD RX 6800
16 GB VRAM • 512 GB/s
AMD
$599
AmazonNeweggeBayPCPartPicker
Intel Arc A770 16GB
16 GB VRAM • 560 GB/s
INTEL
$349
AmazonNeweggeBayPCPartPicker
Apple M1 Pro (16GB)
16 GB VRAM • 200 GB/s
APPLE
$999
Apple M2 Pro (16GB)
16 GB VRAM • 200 GB/s
APPLE
$1299
Apple M4 (16GB)
16 GB VRAM • 120 GB/s
APPLE
$499
NVIDIA Tesla T4 16GB
16 GB VRAM • 320 GB/s
NVIDIA
$800
NVIDIA V100 PCIe 16GB
16 GB VRAM • 900 GB/s
NVIDIA
$2000
AMD RX 9070 XT
16 GB VRAM • 640 GB/s
AMD
$599
AmazonNeweggeBayPCPartPicker
AMD RX 9070
16 GB VRAM • 672 GB/s
AMD
$549
AmazonNeweggeBayPCPartPicker
Apple M1 (16GB)
16 GB VRAM • 68.25 GB/s
APPLE
$699
Apple M2 (16GB)
16 GB VRAM • 100 GB/s
APPLE
$799
Apple M3 (16GB)
16 GB VRAM • 100 GB/s
APPLE
$799
NVIDIA RTX 5060 Ti 16GB
16 GB VRAM • 448 GB/s
NVIDIA
$429
AmazonNeweggeBayPCPartPicker
NVIDIA Tesla P100 DGXS
16 GB VRAM • 732 GB/s
NVIDIA
NVIDIA Tesla P100 PCIe 16 GB
16 GB VRAM • 732 GB/s
NVIDIA
NVIDIA Tesla P100 SXM2
16 GB VRAM • 732 GB/s
NVIDIA
NVIDIA Tesla V100 PCIe 16 GB
16 GB VRAM • 897 GB/s
NVIDIA
NVIDIA Tesla V100 SXM2 16 GB
16 GB VRAM • 1130 GB/s
NVIDIA

Find the best GPU for Magistral Small 24B

Build Hardware for Magistral Small 24B
▸ SPEC SHEET

Magistral Small 24B — 24B Dense.

▸ SPECIFICATIONS
PARAMETERS
24B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
128K tokens
CAPABILITIES
chat, reasoning, coding
RELEASE DATE
2025-06-01
PROVIDER
Mistral AI
FAMILY
mistral
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q3_K_M412.5 GB88%
Q3_K_L4.313.4 GB90%
IQ4_XS4.4613.9 GB92%
Q4_K_S4.6714.5 GB93%
Q4_K_M4.8915.2 GB94%
Q5_K_S5.5717.2 GB96%
Q5_K_M5.717.6 GB96%
Q6_K6.5620.2 GB97%
Q8_08.526.0 GB100%
FP161648.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO49.4
MATH35.6
IFEval65.7
BBH52.8
GPQA18.6
MUSR17.1
BigCodeBench36.1
LiveCodeBench55.8
AIME70.7
GPQA Diamond68.2
§ 02RUN COMMAND

Run Magistral Small 24B locally with Ollama — needs 15.2 GB VRAM at Q4_K_M:

$ollama run magistral:24b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
NVIDIA RTX 5080
16 GB · 960 GB/s
NVIDIA RTX 5070 Ti
16 GB · 896 GB/s
NVIDIA RTX 4080 SUPER
16 GB · 736 GB/s
NVIDIA RTX 4080
16 GB · 717 GB/s
NVIDIA RTX 4070 Ti SUPER
16 GB · 672 GB/s
NVIDIA RTX 4060 Ti 16GB
16 GB · 288 GB/s
AMD RX 7900 GRE
16 GB · 576 GB/s
AMD RX 7800 XT
16 GB · 624 GB/s
AMD RX 7600 XT
16 GB · 288 GB/s
AMD RX 6950 XT
16 GB · 576 GB/s
AMD RX 6900 XT
16 GB · 512 GB/s
AMD RX 6800 XT
16 GB · 512 GB/s
AMD RX 6800
16 GB · 512 GB/s
Intel Arc A770 16GB
16 GB · 560 GB/s
Apple M1 Pro (16GB)
16 GB · 200 GB/s