Allen Institute/Dense

Allen InstituteOLMo-2-0325-32B

chat
32.2B
Parameters
4K
Context length
15
Benchmarks
14
Quantizations
7K
HF downloads
Architecture
Dense
Released
2025-06-15
Layers
64
KV Heads
8
Head Dim
128
Family
olmo

Quantization Options

QuantBitsVRAMQuality
IQ3_XXS3.2513.6 GBlow
IQ3_XS3.514.6 GBlow
Q3_K_S3.6415.1 GBlow
IQ3_M3.7615.6 GBlow
Q3_K_M416.6 GBlow
Q3_K_L4.317.8 GBmoderate
IQ4_XS4.4618.4 GBmoderate
Q4_K_S4.6719.3 GBmoderate
Q4_K_M4.8920.2 GBgood
Q5_K_S5.5722.9 GBgood
Q5_K_M5.723.4 GBgood
Q6_K6.5626.9 GBexcellent
Q8_08.534.7 GBlossless
FP161664.9 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 OLMO-2-0325-32B NOW

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

Community Ratings

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Benchmarks (15)

Arena Elo1222
MATH93.4
IFEval88.8
HumanEval86.7
BBH84.0
AIME77.3
AA Math77.3
LiveCodeBench69.5
MBPP65.1
alpacaeval59.8
GPQA Diamond53.9
GPQA48.6
AA Intelligence12.2
AA Coding5.6
HLE4.9

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run olmo:32b-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 RTX 4090
24 GB VRAM • 1008 GB/s
NVIDIA
$1599
NVIDIA RTX 3090 Ti
24 GB VRAM • 1008 GB/s
NVIDIA
$999
NVIDIA RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$850
AMD RX 7900 XTX
24 GB VRAM • 960 GB/s
AMD
$999
Apple M4 Pro (24GB)
24 GB VRAM • 273 GB/s
APPLE
$1399
NVIDIA L4 24GB
24 GB VRAM • 300 GB/s
NVIDIA
$2500
NVIDIA A10 24GB
24 GB VRAM • 600 GB/s
NVIDIA
$3500
Apple M2 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M3 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M4 (24GB)
24 GB VRAM • 120 GB/s
APPLE
$699
NVIDIA Tesla M40 24 GB
24 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla P10
24 GB VRAM • 694 GB/s
NVIDIA
NVIDIA Tesla P40
24 GB VRAM • 347 GB/s
NVIDIA
NVIDIA Quadro RTX 6000
24 GB VRAM • 672 GB/s
NVIDIA
$4000
NVIDIA GeForce RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$1499
NVIDIA A10 PCIe
24 GB VRAM • 600 GB/s
NVIDIA
NVIDIA A10G
24 GB VRAM • 600 GB/s
NVIDIA
NVIDIA RTX A5000
24 GB VRAM • 768 GB/s
NVIDIA
$2500
NVIDIA GeForce RTX 4090
24 GB VRAM • 1010 GB/s
NVIDIA
$1599
NVIDIA L40 CNX
24 GB VRAM • 864 GB/s
NVIDIA
$5000
NVIDIA L40G
24 GB VRAM • 864 GB/s
NVIDIA
$5000
NVIDIA A30 PCIe
24 GB VRAM • 933 GB/s
NVIDIA
NVIDIA A30X
24 GB VRAM • 1220 GB/s
NVIDIA

Find the best GPU for OLMo-2-0325-32B

Build Hardware for OLMo-2-0325-32B
▸ SPEC SHEET

OLMo-2-0325-32B32.2B Dense.

▸ SPECIFICATIONS
PARAMETERS
32.2B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
4K tokens
CAPABILITIES
chat
RELEASE DATE
2025-06-15
PROVIDER
Allen Institute
FAMILY
olmo
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2513.6 GB82%
IQ3_XS3.514.6 GB84%
Q3_K_S3.6415.1 GB85%
IQ3_M3.7615.6 GB86%
Q3_K_M416.6 GB88%
Q3_K_L4.317.8 GB90%
IQ4_XS4.4618.4 GB92%
Q4_K_S4.6719.3 GB93%
Q4_K_M4.8920.2 GB94%
Q5_K_S5.5722.9 GB96%
Q5_K_M5.723.4 GB96%
Q6_K6.5626.9 GB97%
Q8_08.534.7 GB100%
FP161664.9 GB100%
§ 01BENCHMARK SCORES
HumanEval86.7
MATH93.4
IFEval88.8
BBH84.0
GPQA48.6
MBPP65.1
alpacaeval59.8
Arena Elo1222.0
GPQA Diamond53.9
HLE4.9
AA Intelligence12.2
AA Coding5.6
LiveCodeBench69.5
AIME77.3
AA Math77.3
§ 02RUN COMMAND

Run OLMo-2-0325-32B locally with Ollama — needs 20.2 GB VRAM at Q4_K_M:

$ollama run olmo:32b