FITMYLLM · JULY 28, 2026 · OPEN METHODOLOGY · COMMUNITY BENCHMARKS
LIVE · UPDATED DAILY
32B
Parameters (8B active)
Quantization Options Select your GPU for speed estimates Context length: 4K 8K 16K 32K 64K 125K
Quant Bits VRAM @ 16K Quality IQ3_XXS 3.25 15.4 GB
13.5 + 1.9 KV
low IQ3_XS 3.5 16.4 GB
14.5 + 1.9 KV
low Q3_K_S 3.64 16.9 GB
15.0 + 1.9 KV
low IQ3_M 3.76 17.4 GB
15.5 + 1.9 KV
low Q3_K_M 4 18.4 GB
16.5 + 1.9 KV
low Q3_K_L 4.3 19.6 GB
17.7 + 1.9 KV
moderate IQ4_XS 4.46 20.2 GB
18.3 + 1.9 KV
moderate Q4_K_S 4.67 21.0 GB
19.2 + 1.9 KV
moderate Q4_K_M 4.89 21.9 GB
20.0 + 1.9 KV
good Q5_K_S 5.57 24.6 GB
22.8 + 1.9 KV
good Q5_K_M 5.7 25.2 GB
23.3 + 1.9 KV
good Q6_K 6.56 28.6 GB
26.7 + 1.9 KV
excellent Q8_0 8.5 36.4 GB
34.5 + 1.9 KV
lossless FP16 16 66.4 GB
64.5 + 1.9 KV
lossless
Select your GPU above to see speed estimates and compatibility for each quantization.
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Community Ratings Chat Coding Reasoning Creative Vision Roleplay Agentic
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Run this model IQ3_XXS — 13.5 GB VRAM IQ3_XS — 14.5 GB VRAM Q3_K_S — 15.0 GB VRAM IQ3_M — 15.5 GB VRAM Q3_K_M — 16.5 GB VRAM Q3_K_L — 17.7 GB VRAM IQ4_XS — 18.3 GB VRAM Q4_K_S — 19.2 GB VRAM Q4_K_M — 20.0 GB VRAM Q5_K_S — 22.8 GB VRAM Q5_K_M — 23.3 GB VRAM Q6_K — 26.7 GB VRAM Q8_0 — 34.5 GB VRAM FP16 — 64.5 GB VRAM
Ollama llama.cpp vLLM LM Studio KoboldCpp Jan Docker
▸ Easiest way to get started · Beginners
DOCS ↗ curl -fsSL https://ollama.com/install.sh | shCOPY
$ ollama run granite:32b-q4_K_MCOPY
Tag may need adjustment — check ollama.com/library/granite 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.
Auto-detect GPU Live tok/s in chat Speed benchmarks 9 inference engines
GPUs that can run this model At Q4_K_M quantization. Sorted by minimum VRAM.
Find the best GPU for Granite 4.0 Small
Build Hardware for Granite 4.0 Small Granite 4.0 Small — strong enterprise MoE model with multilingual support.
Read full model card ▸ COLOPHON FITMYLLM · INDEPENDENT · DATA-DRIVEN
FITMYLLM · EST. 2025 · © 2026
RECOMMENDATIONS FROM PUBLISHED MATH, CORRECTED BY THE COMMUNITY — 30.
▸ SPEC SHEET
Granite 4.0 Small — 32B MoE. ▸ SPECIFICATIONS
PARAMETERS 32B (8B active)
ARCHITECTURE Mixture of Experts
CONTEXT LENGTH 125K tokens
CAPABILITIES chat, coding, multilingual
RELEASE DATE 2025-10-02
PROVIDER IBM
FAMILY granite ▸ VRAM REQUIREMENTS
QUANT BPW VRAM QUALITY IQ3_XXS 3.25 13.5 GB 82% IQ3_XS 3.5 14.5 GB 84% Q3_K_S 3.64 15.0 GB 85% IQ3_M 3.76 15.5 GB 86% Q3_K_M 4 16.5 GB 88% Q3_K_L 4.3 17.7 GB 90% IQ4_XS 4.46 18.3 GB 92% Q4_K_S 4.67 19.2 GB 93% Q4_K_M 4.89 20.0 GB 94% Q5_K_S 5.57 22.8 GB 96% Q5_K_M 5.7 23.3 GB 96% Q6_K 6.56 26.7 GB 97% Q8_0 8.5 34.5 GB 100% FP16 16 64.5 GB 100%
§ 01 BENCHMARK SCORES
HumanEval 88.0
IFEval 87.6
BBH 81.6
GPQA 40.6
MBPP 84.0
BigCodeBench 46.2
§ 03 COMPATIBLE GPUs
30 @ Q4_K_M Feedback 