FitMyLLM
KRAFTON/Mixture of Experts

KRaon-1 mini (preview)

Raon-1 mini (preview) — KRAFTON's first in-house LLM, a 28.8B MoE with 4.3B active, strongest in Korean. 18 of its 25 layers are linear Raon Delta Attention with a fixed-size state; only 7 MLA layers keep a KV cache, about 8 KiB per token.

chatreasoningmultilingualmathagentictool_use
28.78B
Parameters (4.3B active)
256K
Context length
5
Benchmarks
10
Quantizations
4K
HF downloads
Architecture
MoE
Released
2026-10-21
Layers
25
KV Heads
40
Head Dim
128
Family
other

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q3_K_M4
15.0 GB
14.9 + 0.1 KV
low
Q3_K_L4.3
16.0 GB
16.0 + 0.1 KV
moderate
IQ4_XS4.46
16.6 GB
16.5 + 0.1 KV
moderate
Q4_K_S4.67
17.4 GB
17.3 + 0.1 KV
moderate
Q4_K_M4.89
18.2 GB
18.1 + 0.1 KV
good
Q5_K_S5.57
20.6 GB
20.5 + 0.1 KV
good
Q5_K_M5.7
21.1 GB
21.0 + 0.1 KV
good
Q6_K6.56
24.2 GB
24.1 + 0.1 KV
excellent
Q8_08.5
31.1 GB
31.1 + 0.1 KV
lossless
FP1616
58.1 GB
58.0 + 0.1 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 →
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Community Ratings

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Benchmarks (5)

AIME93.3
GPQA Diamond84.3
LiveCodeBench81.6
MMLU-PRO76.5
SWE-bench70.8

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run other:29b-q4_K_M

Tag may need adjustment — check ollama.com/library/other 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

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA RTX A4500
20 GB VRAM • 640 GB/s
NVIDIA
$2000
Apple M4 Pro (24GB)
24 GB VRAM • 273 GB/s
APPLE
$1399
NVIDIA L4 24GB
24 GB VRAM • 300 GB/s
NVIDIA
$2500
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 RTX A5000
24 GB VRAM • 768 GB/s
NVIDIA
$2500
NVIDIA L40 CNX
24 GB VRAM • 864 GB/s
NVIDIA
$5000

Find the best GPU for Raon-1 mini (preview)

Build Hardware for Raon-1 mini (preview)
▸ SPEC SHEET

Raon-1 mini (preview) — 28.78B MoE.

▸ SPECIFICATIONS
PARAMETERS
28.78B (4.3B active)
ARCHITECTURE
Mixture of Experts
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, reasoning, multilingual, math, agentic, tool_use
RELEASE DATE
2026-10-21
PROVIDER
KRAFTON
FAMILY
other
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q3_K_M414.9 GB88%
Q3_K_L4.316.0 GB90%
IQ4_XS4.4616.5 GB92%
Q4_K_S4.6717.3 GB93%
Q4_K_M4.8918.1 GB94%
Q5_K_S5.5720.5 GB96%
Q5_K_M5.721.0 GB96%
Q6_K6.5624.1 GB97%
Q8_08.531.1 GB100%
FP161658.0 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO76.5
GPQA Diamond84.3
LiveCodeBench81.6
AIME93.3
SWE-bench70.8
§ 03COMPATIBLE GPUs
30 @ Q4_K_M