Google/Dense

GoogleRecurrentGemma 9B

Griffin architecture — fixed-state recurrence, not attention. Constant RAM usage.

chat
9B
Parameters
8K
Context length
7
Benchmarks
6
Quantizations
Architecture
Dense
Released
2024-04-01
Layers
42
KV Heads
1
Head Dim
256
Family
gemma

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.896.0 GBgood
Q5_K_S5.576.8 GBgood
Q5_K_M5.76.9 GBgood
Q6_K6.567.9 GBexcellent
Q8_08.510.1 GBlossless
FP161618.5 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 RECURRENTGEMMA 9B NOW

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

Community Ratings

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Benchmarks (7)

IFEval80.5
BBH44.2
MMLU-PRO37.4
BigCodeBench34.7
MATH23.3
GPQA12.8
MUSR12.2

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run recurrentgemma:9b-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.

NVIDIA RTX 3050 6GB
6 GB VRAM • 168 GB/s
NVIDIA
$169
Intel Arc A380
6 GB VRAM • 186 GB/s
INTEL
$129
NVIDIA RTX 2060 6GB
6 GB VRAM • 336 GB/s
NVIDIA
$150
NVIDIA GTX 1660 Ti
6 GB VRAM • 288 GB/s
NVIDIA
$140
NVIDIA Tesla C2070
6 GB VRAM • 143 GB/s
NVIDIA
NVIDIA Tesla C2075
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla C2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla M2070
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2070-Q
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2075
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla X2070
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla X2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla K20X
6 GB VRAM • 250 GB/s
NVIDIA
NVIDIA Tesla K20Xm
6 GB VRAM • 250 GB/s
NVIDIA

Find the best GPU for RecurrentGemma 9B

Build Hardware for RecurrentGemma 9B
▸ SPEC SHEET

RecurrentGemma 9B9B Dense.

▸ SPECIFICATIONS
PARAMETERS
9B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
8K tokens
CAPABILITIES
chat
RELEASE DATE
2024-04-01
PROVIDER
Google
FAMILY
gemma
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.896.0 GB94%
Q5_K_S5.576.8 GB96%
Q5_K_M5.76.9 GB96%
Q6_K6.567.9 GB97%
Q8_08.510.1 GB100%
FP161618.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO37.4
MATH23.3
IFEval80.5
BBH44.2
GPQA12.8
MUSR12.2
BigCodeBench34.7
§ 02RUN COMMAND

Run RecurrentGemma 9B locally with Ollama — needs 6.0 GB VRAM at Q4_K_M:

$ollama run recurrentgemma:9b