FitMyLLM
MBZUAI IFM/Mixture of Experts

MK2 Horizon MoVA 36B-A4B

K2 Horizon MoVA 36B-A4B is the sparse mid-size of MBZUAI IFM's fully open K2 Horizon family: a 36B MoE with 4B active, using a mixture-of-values attention design, with a 512K context.

chatcodingreasoningmathagentictool_use
37.44B
Parameters (4B active)
512K
Context length
6
Benchmarks
14
Quantizations
14K
HF downloads
Architecture
MoE
Released
2026-09-03
Layers
48
KV Heads
8
Head Dim
128
Family
other

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
IQ3_XXS3.25
17.9 GB
15.7 + 2.3 KV
low
IQ3_XS3.5
19.1 GB
16.9 + 2.3 KV
low
Q3_K_S3.64
19.8 GB
17.5 + 2.3 KV
low
IQ3_M3.76
20.3 GB
18.1 + 2.3 KV
low
Q3_K_M4
21.5 GB
19.2 + 2.3 KV
low
Q3_K_L4.3
22.9 GB
20.6 + 2.3 KV
moderate
IQ4_XS4.46
23.6 GB
21.4 + 2.3 KV
moderate
Q4_K_S4.67
24.6 GB
22.3 + 2.3 KV
moderate
Q4_K_M4.89
25.6 GB
23.4 + 2.3 KV
good
Q5_K_S5.57
28.8 GB
26.6 + 2.3 KV
good
Q5_K_M5.7
29.4 GB
27.2 + 2.3 KV
good
Q6_K6.56
33.4 GB
31.2 + 2.3 KV
excellent
Q8_08.5
42.5 GB
40.3 + 2.3 KV
lossless
FP1616
77.6 GB
75.4 + 2.3 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 (6)

GPQA Diamond82.2
AA Long Context71.7
Terminal-Bench 2.156.6
SciCode40.0
HLE23.4
Terminal-Bench 40.0

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run other:37b-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.

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
NVIDIA L40G
24 GB VRAM • 864 GB/s
NVIDIA
$5000

Find the best GPU for K2 Horizon MoVA 36B-A4B

Build Hardware for K2 Horizon MoVA 36B-A4B
▸ SPEC SHEET

K2 Horizon MoVA 36B-A4B — 37.44B MoE.

▸ SPECIFICATIONS
PARAMETERS
37.44B (4B active)
ARCHITECTURE
Mixture of Experts
CONTEXT LENGTH
512K tokens
CAPABILITIES
chat, coding, reasoning, math, agentic, tool_use
RELEASE DATE
2026-09-03
PROVIDER
MBZUAI IFM
FAMILY
other
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2515.7 GB82%
IQ3_XS3.516.9 GB84%
Q3_K_S3.6417.5 GB85%
IQ3_M3.7618.1 GB86%
Q3_K_M419.2 GB88%
Q3_K_L4.320.6 GB90%
IQ4_XS4.4621.4 GB92%
Q4_K_S4.6722.3 GB93%
Q4_K_M4.8923.4 GB94%
Q5_K_S5.5726.6 GB96%
Q5_K_M5.727.2 GB96%
Q6_K6.5631.2 GB97%
Q8_08.540.3 GB100%
FP161675.4 GB100%
§ 01BENCHMARK SCORES
GPQA Diamond82.2
HLE23.4
aa_scicode40.0
aa_lcr71.7
aa_terminal_bench_v256.6
aa_terminal_bench_v40.0
§ 03COMPATIBLE GPUs
30 @ Q4_K_M