FitMyLLM
Google/Dense

GoogleGemma 4 31B

Gemma 4 31B — Google's most capable open model. Dense 31B with 256K context, vision, and thinking mode.

chatcodingreasoningmultilingualvision
31B
Parameters
256K
Context length
19
Benchmarks
14
Quantizations
500K
HF downloads
Architecture
Dense
Released
2026-04-02
Layers
60
KV Heads
16
Head Dim
256
Family
gemma

Quantization Options

QuantBitsVRAMQuality
IQ3_XXS3.2513.1 GBlow
IQ3_XS3.514.1 GBlow
Q3_K_S3.6414.6 GBlow
IQ3_M3.7615.1 GBlow
Q3_K_M416.0 GBlow
Q3_K_L4.317.2 GBmoderate
IQ4_XS4.4617.8 GBmoderate
Q4_K_S4.6718.6 GBmoderate
Q4_K_M4.8919.4 GBgood
Q5_K_S5.5722.1 GBgood
Q5_K_M5.722.6 GBgood
Q6_K6.5625.9 GBexcellent
Q8_08.533.4 GBlossless
FP161662.5 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 GEMMA 4 31B NOW

Rent on RunPod →Or Vast.ai →

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

Community Ratings

Loading ratings...

Benchmarks (19)

Arena Elo1452
AIME89.2
MMLU-PRO85.2
GPQA Diamond84.3
LiveCodeBench80.0
IFBench75.6
IFEval75.5
BBH74.4
AA Long Context62.0
τ²-Bench59.9
SciCode43.4
BigCodeBench42.8
AA Intelligence39.2
AA Coding38.7
Terminal-Bench36.4
MATH27.9
HLE19.5
MUSR16.9
GPQA16.0

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run gemma4:31b-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
HuggingFaceOllama LibraryGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

AMD RX 7900 XT
20 GB VRAM • 800 GB/s
AMD
$849
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4000 Ada 20GB
20 GB VRAM • 432 GB/s
NVIDIA
$1250
AmazonNeweggeBayPCPartPicker
NVIDIA A10M
20 GB VRAM • 500 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 3080 Ti 20 GB
20 GB VRAM • 760 GB/s
NVIDIA
$1199
AmazonNeweggeBayPCPartPicker
AMD Radeon RX 7900 XT
20 GB VRAM • 800 GB/s
AMD
$899
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4000 Ada Generation
20 GB VRAM • 360 GB/s
NVIDIA
$1250
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4000 SFF Ada Generation
20 GB VRAM • 280 GB/s
NVIDIA
$1250
AmazonNeweggeBayPCPartPicker
NVIDIA RTX A4500
20 GB VRAM • 640 GB/s
NVIDIA
$2000
NVIDIA RTX 4090
24 GB VRAM • 1008 GB/s
NVIDIA
$1599
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 3090 Ti
24 GB VRAM • 1008 GB/s
NVIDIA
$999
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$850
AmazonNeweggeBayPCPartPicker
AMD RX 7900 XTX
24 GB VRAM • 960 GB/s
AMD
$999
AmazonNeweggeBayPCPartPicker
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
AmazonNeweggeBayPCPartPicker
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
AmazonNeweggeBayPCPartPicker
NVIDIA Quadro RTX 6000 Passive
24 GB VRAM • 624 GB/s
NVIDIA
$4000
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$1499
AmazonNeweggeBayPCPartPicker
NVIDIA A10 PCIe
24 GB VRAM • 600 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA A10G
24 GB VRAM • 600 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA RTX A5000
24 GB VRAM • 768 GB/s
NVIDIA
$2500
NVIDIA GeForce RTX 3090 Ti
24 GB VRAM • 1010 GB/s
NVIDIA
$1999
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 4090
24 GB VRAM • 1010 GB/s
NVIDIA
$1599
AmazonNeweggeBayPCPartPicker
NVIDIA L40 CNX
24 GB VRAM • 864 GB/s
NVIDIA
$5000

Find the best GPU for Gemma 4 31B

Build Hardware for Gemma 4 31B
▸ SPEC SHEET

Gemma 4 31B — 31B Dense.

▸ SPECIFICATIONS
PARAMETERS
31B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, coding, reasoning, multilingual, vision
RELEASE DATE
2026-04-02
PROVIDER
Google
FAMILY
gemma
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2513.1 GB82%
IQ3_XS3.514.1 GB84%
Q3_K_S3.6414.6 GB85%
IQ3_M3.7615.1 GB86%
Q3_K_M416.0 GB88%
Q3_K_L4.317.2 GB90%
IQ4_XS4.4617.8 GB92%
Q4_K_S4.6718.6 GB93%
Q4_K_M4.8919.4 GB94%
Q5_K_S5.5722.1 GB96%
Q5_K_M5.722.6 GB96%
Q6_K6.5625.9 GB97%
Q8_08.533.4 GB100%
FP161662.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO85.2
MATH27.9
IFEval75.5
BBH74.4
GPQA16.0
MUSR16.9
BigCodeBench42.8
Arena Elo1452.0
GPQA Diamond84.3
HLE19.5
AA Intelligence39.2
AA Coding38.7
LiveCodeBench80.0
AIME89.2
aa_ifbench75.6
aa_terminal_bench36.4
aa_tau259.9
aa_scicode43.4
aa_lcr62.0
§ 02RUN COMMAND

Run Gemma 4 31B locally with Ollama — needs 19.4 GB VRAM at Q4_K_M:

$ollama run gemma4:31b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
AMD RX 7900 XT
20 GB · 800 GB/s
NVIDIA RTX 4000 Ada 20GB
20 GB · 432 GB/s
NVIDIA A10M
20 GB · 500 GB/s
NVIDIA GeForce RTX 3080 Ti 20 GB
20 GB · 760 GB/s
AMD Radeon RX 7900 XT
20 GB · 800 GB/s
NVIDIA RTX 4000 Ada Generation
20 GB · 360 GB/s
NVIDIA RTX 4000 SFF Ada Generation
20 GB · 280 GB/s
NVIDIA RTX A4500
20 GB · 640 GB/s
NVIDIA RTX 4090
24 GB · 1008 GB/s
NVIDIA RTX 3090 Ti
24 GB · 1008 GB/s
NVIDIA RTX 3090
24 GB · 936 GB/s
AMD RX 7900 XTX
24 GB · 960 GB/s
Apple M4 Pro (24GB)
24 GB · 273 GB/s
NVIDIA L4 24GB
24 GB · 300 GB/s
NVIDIA A10 24GB
24 GB · 600 GB/s