exaone/Dense

EEXAONE Deep 2.4B

reasoningmathcoding
2.4B
Parameters
32K
Context length
6
Benchmarks
6
Quantizations
Architecture
Dense
Released
2025-03-16
Layers
30
KV Heads
8
Head Dim
128
Family
exaone

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.892.0 GBgood
Q5_K_S5.572.2 GBgood
Q5_K_M5.72.2 GBgood
Q6_K6.562.5 GBexcellent
Q8_08.53.0 GBlossless
FP16165.3 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 EXAONE DEEP 2.4B NOW

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

Community Ratings

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Benchmarks (6)

IFEval79.5
MATH36.8
MMLU-PRO25.3
BBH15.9
MUSR3.2
GPQA2.1

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run exaone-deep:2.4b-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.

Find the best GPU for EXAONE Deep 2.4B

Build Hardware for EXAONE Deep 2.4B
▸ SPEC SHEET

EXAONE Deep 2.4B2.4B Dense.

▸ SPECIFICATIONS
PARAMETERS
2.4B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
32K tokens
CAPABILITIES
reasoning, math, coding
RELEASE DATE
2025-03-16
FAMILY
exaone
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.892.0 GB94%
Q5_K_S5.572.2 GB96%
Q5_K_M5.72.2 GB96%
Q6_K6.562.5 GB97%
Q8_08.53.0 GB100%
FP16165.3 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO25.3
MATH36.8
IFEval79.5
BBH15.9
GPQA2.1
MUSR3.2
§ 02RUN COMMAND

Run EXAONE Deep 2.4B locally with Ollama — needs 2.0 GB VRAM at Q4_K_M:

$ollama run exaone-deep:2.4b