v2.2 · 2026-06-12
Gemma 2 9B Instruct
gemma-2-9b-it
Gemma 2 9B Instruct is a 9B text chat model profile for local AI planning. This page records provider, license, context, quantization, hardware-fit estimates, setup hints, source links, and caveats so readers do not choose a model by name alone.
PROVIDER
Google
FAMILY
Gemma 2
MODEL TYPE
text-chat
PARAMETERS
9B
MODALITIES
text
ARCHITECTURE
decoder-only Transformer text-to-text language model
CONTEXT WINDOW
8,192 tokens
TRAINING TOKENS
8.0T
RELEASE DATE
2024-06-27
GGUF REPOSITORIES
bartowski/gemma-2-9b-it-GGUF community conversion
Community llama.cpp GGUF quantization of the official Google instruction-tuned checkpoint.
SETUP HINTS
OLLAMA
ollama run gemma2LM STUDIO
Search for bartowski/gemma-2-9b-it-GGUF and select Q4_K_M or Q5_K_M.
LLAMA.CPP
Use hf.co/bartowski/gemma-2-9b-it-GGUF:Q4_K_M; increase context only if memory permits.QUANTIZATION FILE SIZES (GGUF)
Q4_K_M
5.76 GB
Q5_K_M
6.65 GB
Q8_0
9.83 GB
Quantization note: Q4_K_M for default local use; Q5_K_M if the model still fits comfortably in RAM/VRAM.
RAM / VRAM ESTIMATES
MIN RAM
10 GB
COMFORTABLE RAM
16 GB
MIN VRAM
8 GB
COMFORTABLE VRAM
12 GB
These are conservative local-inference estimates, not official hardware requirements.
HARDWARE FIT
CPU only (no GPU)
slow
8 GB RAM
no
16 GB RAM
yes
32 GB RAM
yes
8 GB VRAM
borderline
12 GB VRAM
yes
24 GB VRAM
yes
Apple Silicon (unified memory)
yes
Hardware fit values are conservative local-inference estimates based on GGUF size plus runtime and KV-cache overhead. Actual requirements depend on context length, quantization, runtime, GPU offload, and other running apps.
BEST FOR
·general local chat
·summarization
·drafting
·offline assistant use
AVOID IF
·image input is required
·8GB system RAM is the hard ceiling
·native tool/function calling is required
CAVEATS
·Gemma 2 is text-only; do not treat it as a vision-language model.
·GGUF files are community conversions, not official Google GGUF releases.
·RAM and VRAM figures are estimates based on GGUF file size plus conservative runtime and KV-cache overhead, not official hardware requirements.
SOURCE URLS
FIELD EVIDENCE
licenseai.google.dev/gemma/terms
architectureai.google.dev/gemma/docs/core/model_card_2
contextWindowTokensdevelopers.googleblog.com/gemma-explained-overview-gemma-model-family-architectures/
trainingTokensai.google.dev/gemma/docs/core/model_card_2
releaseDateai.google.dev/gemma/docs/releases
hfGgufReposhuggingface.co/bartowski/gemma-2-9b-it-GGUF
q4FileSizeGbhuggingface.co/bartowski/gemma-2-9b-it-GGUF
q5FileSizeGbhuggingface.co/bartowski/gemma-2-9b-it-GGUF
q8FileSizeGbhuggingface.co/bartowski/gemma-2-9b-it-GGUF
hardwareEstimateshuggingface.co/bartowski/gemma-2-9b-it-GGUF
LANGUAGES
English
CAPABILITIES
No special capabilities flagged.