FitMyLLM
Mistral AI/Dense

Mistral AIPixtral Large 124B

Pixtral Large 124B — most capable Mistral vision model. Strong reasoning with images.

chatvisionreasoningThinkingTool Use
124B
Parameters
128K
Context length
20
Benchmarks
17
Quantizations
20K
HF downloads
Architecture
Dense
Released
2024-11-18
Layers
88
KV Heads
8
Head Dim
128
Family
mistral

Quantization Options

QuantBitsVRAMQuality
IQ2_XXS2.3837.4 GBlow
IQ2_M2.9345.9 GBlow
Q2_K3.1649.5 GBlow
IQ3_XXS3.2550.9 GBlow
IQ3_XS3.554.7 GBlow
Q3_K_S3.6456.9 GBlow
IQ3_M3.7658.8 GBlow
Q3_K_M462.5 GBlow
Q3_K_L4.367.1 GBmoderate
IQ4_XS4.4669.6 GBmoderate
Q4_K_S4.6772.9 GBmoderate
Q4_K_M4.8976.3 GBgood
Q5_K_S5.5786.8 GBgood
Q5_K_M5.788.8 GBgood
Q6_K6.56102.2 GBexcellent
Q8_08.5132.2 GBlossless
FP1616248.5 GBlossless

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

▸ READY TO RUN THIS?RENT BY THE HOUR

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Community Ratings

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Benchmarks (20)

IFEval87.0
HumanEval82.0
MMBench79.0
MATH-50071.4
MMMU62.7
BBH52.7
MMLU-PRO50.7
GPQA Diamond50.5
MATH49.5
τ²-Bench36.5
IFBench34.5
SciCode29.2
LiveCodeBench26.1
GPQA24.9
MUSR17.2
AA Intelligence14.0
AA Long Context10.3
HLE3.6
AIME2.3
AA Math2.3

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run mistral:124b-q4_K_M

Tag may need adjustment — check ollama.com/library/mistral for available tags.

▸ 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
HuggingFaceGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA H100 SXM5 80GB
80 GB VRAM • 3350 GB/s
NVIDIA
$25000
NVIDIA H100 PCIe 80GB
80 GB VRAM • 2000 GB/s
NVIDIA
$25000
NVIDIA A100 SXM 80GB
80 GB VRAM • 2039 GB/s
NVIDIA
$10000
NVIDIA A100 PCIe 80GB
80 GB VRAM • 1935 GB/s
NVIDIA
$10000
NVIDIA A100 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$15000
NVIDIA A100 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
$10000
NVIDIA A100X
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H100 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 80 GB
80 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 CNX
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA A800 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
NVIDIA A800 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 SXM5
80 GB VRAM • 3360 GB/s
NVIDIA
NVIDIA RTX 6000D
84 GB VRAM • 1570 GB/s
NVIDIA
$7500
NVIDIA B200
90 GB VRAM • 4100 GB/s
NVIDIA
$30000
NVIDIA H100 NVL 94 GB
94 GB VRAM • 3940 GB/s
NVIDIA
$30000
NVIDIA H100 SXM5 94 GB
94 GB VRAM • 3360 GB/s
NVIDIA
$25000
RTX Pro 6000
96 GB VRAM • 1792 GB/s
NVIDIA
$8565
NVIDIA H100 PCIe 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
Intel Data Center GPU Max 1350
96 GB VRAM • 2460 GB/s
INTEL
NVIDIA RTX PRO 6000 Blackwell Server
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
NVIDIA RTX PRO 6000 Blackwell
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
AMD Instinct MI300A
120 GB VRAM • 5300 GB/s
AMD
$12000
Apple M4 Max (128GB)
128 GB VRAM • 546 GB/s
APPLE
$3999
AMD Instinct MI250X
128 GB VRAM • 3277 GB/s
AMD
$10000
Apple M1 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$4999
Apple M2 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$3999
AMD Radeon Instinct MI250
128 GB VRAM • 3280 GB/s
AMD
$12000

Find the best GPU for Pixtral Large 124B

Build Hardware for Pixtral Large 124B

Model Card

View on HuggingFace

Pixtral Large 124B — most capable Mistral vision model. Strong reasoning with images.

▸ SPEC SHEET

Pixtral Large 124B — 124B Dense.

▸ SPECIFICATIONS
PARAMETERS
124B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
128K tokens
CAPABILITIES
chat, vision, reasoning
RELEASE DATE
2024-11-18
PROVIDER
Mistral AI
FAMILY
mistral
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ2_XXS2.3837.4 GB65%
IQ2_M2.9345.9 GB75%
Q2_K3.1649.5 GB78%
IQ3_XXS3.2550.9 GB82%
IQ3_XS3.554.7 GB84%
Q3_K_S3.6456.9 GB85%
IQ3_M3.7658.8 GB86%
Q3_K_M462.5 GB88%
Q3_K_L4.367.1 GB90%
IQ4_XS4.4669.6 GB92%
Q4_K_S4.6772.9 GB93%
Q4_K_M4.8976.3 GB94%
Q5_K_S5.5786.8 GB96%
Q5_K_M5.788.8 GB96%
Q6_K6.56102.2 GB97%
Q8_08.5132.2 GB100%
FP1616248.5 GB100%
§ 01BENCHMARK SCORES
HumanEval82.0
MMLU-PRO50.7
MATH49.5
IFEval87.0
BBH52.7
MMMU62.7
GPQA24.9
MUSR17.2
MMBench79.0
GPQA Diamond50.5
LiveCodeBench26.1
AIME2.3
MATH-50071.4
HLE3.6
AA Intelligence14.0
AA Math2.3
aa_ifbench34.5
aa_tau236.5
aa_scicode29.2
aa_lcr10.3
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
NVIDIA H100 SXM5 80GB
80 GB · 3350 GB/s
NVIDIA H100 PCIe 80GB
80 GB · 2000 GB/s
NVIDIA A100 SXM 80GB
80 GB · 2039 GB/s
NVIDIA A100 PCIe 80GB
80 GB · 1935 GB/s
NVIDIA A100 SXM4 80 GB
80 GB · 2040 GB/s
NVIDIA A100 PCIe 80 GB
80 GB · 1940 GB/s
NVIDIA A100X
80 GB · 2040 GB/s
NVIDIA H100 PCIe 80 GB
80 GB · 2040 GB/s
NVIDIA H100 SXM5 80 GB
80 GB · 3360 GB/s
NVIDIA H100 CNX
80 GB · 2040 GB/s
NVIDIA A800 PCIe 80 GB
80 GB · 1940 GB/s
NVIDIA A800 SXM4 80 GB
80 GB · 2040 GB/s
NVIDIA H800 PCIe 80 GB
80 GB · 2040 GB/s
NVIDIA H800 SXM5
80 GB · 3360 GB/s
NVIDIA RTX 6000D
84 GB · 1570 GB/s