Home / Models / Gemma 2 9B Instruct / NVIDIA GTX 1080 Ti 11 GB
Can Gemma 2 9B Instruct run on NVIDIA GTX 1080 Ti 11 GB?
Yes. Calculated memory fit: Gemma 2 9B Instruct can run entirely in this GPU’s usable VRAM at one or more supported quantizations.
Can it run?
- Can it run?
- Yes, full GPU fit (calculated estimate).
- Full GPU fit?
- Yes
- Model
- Gemma 2 9B Instruct · 9.2B
- GPU
- NVIDIA GTX 1080 Ti 11 GB · 11 GB advertised
What else can NVIDIA GTX 1080 Ti 11 GB run? · Find other GPUs for Gemma 2 9B Instruct
Memory calculation
Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.
| Model weights | 5.4 GB |
|---|---|
| KV cache | 2.6 GB |
| Runtime reserve | 0.8 GB |
| Safety margin | 0.4 GB |
| Required (estimated) | 9.2 GB |
| GPU usable VRAM | 9.9 GB |
Result: FITS IN VRAM
Quantization table
| Quantization | 2K | 4K | 8K |
|---|---|---|---|
| BF16 | Offload | Offload | Offload |
| FP16 | Offload | Offload | Offload |
| Q3 | Fits | Fits | Fits |
| Q4 | Fits | Fits | Fits |
| Q5 | Fits | Fits | Limited context |
| Q6 | Fits | Limited context | Limited context |
| Q8 | Offload | Offload | Offload |
What fits entirely in VRAM?
- Q3 at 2K context
- Q3 at 4K context
- Q3 at 8K context
- Q4 at 2K context
- Q4 at 4K context
- Q4 at 8K context
- Q5 at 2K context
- Q5 at 4K context
- Q6 at 2K context
What requires RAM offload?
Offload is shown only when the model does not fully fit in usable VRAM but stays within the modeled offload allowance.
Performance
Separate from memory fit. Runtime is llama.cpp · quantization bucket Q4 (GGUF Q4_0 maps to Q4). Workload is llama-bench pp512 / tg128 (short context, batch 1, full GPU offload). This is not a ranking and not a 8K–128K speed claim.
- Model
- Gemma 2 9B Instruct
- GPU
- NVIDIA GTX 1080 Ti 11 GB
- Runtime
- llama.cpp · CUDA · model 1.0.0
- Decode
- ~40 tok/s · Calibrated estimate · MEDIUM confidence (spread ~35 tok/s–~45 tok/s)
- Prefill
- ~830 tok/s at a 512-token prompt · Calibrated estimate · MEDIUM confidence
- Time to first token
- ~617 ms for a 512-token prompt (512 / prefill tok/s). Not estimated at 8K–128K.
decode_tps = GPU_efficiency × memory_bandwidth / model_weight_bytes; efficiency from same-gpu Llama 2 7B Q4_0 efficiency
Available graphics cards
These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.
ASUS ROG-STRIX-GTX1080TI-O11G-GAMING NVIDIA GeForce GTX 1080 Ti 11 GB GDDR5X
11 GB · Amazon unmatched
ASUS ROG-POSEIDON-GTX1080TI-P11G-GAMING NVIDIA GeForce GTX 1080 Ti 11 GB GDDR5X
11 GB · Amazon unmatched
GIGABYTE AORUS XTREME AORUS GeForce GTX 1080 Ti Xtreme Edition 11G
11 GB · Amazon unmatched
ASUS TURBO-GTX1080TI-11G NVIDIA GeForce GTX 1080 Ti 11 GB GDDR5X
11 GB · Amazon unmatched
ASUS ROG-STRIX-GTX1080TI-11G-GAMING NVIDIA GeForce GTX 1080 Ti 11 GB GDDR5X
11 GB · Amazon unmatched
ASUS TURBO-GTX1080TI-11G NVIDIA GeForce GTX 1080 Ti 11 GB GDDR5X
11 GB · Amazon unmatched
GIGABYTE GV-N108TTURBO-11GD graphics card NVIDIA GeForce GTX 1080 Ti 11 GB GDDR5X
11 GB · Amazon unmatched
ASUS ROG-STRIX-GTX1080TI-O11G-GAMING NVIDIA GeForce GTX 1080 Ti 11 GB GDDR5X
11 GB · Amazon unmatched
ASUS ROG-STRIX-GTX1080TI-11G-GAMING graphics card NVIDIA GeForce GTX 1080 Ti 11 GB GDDR5X
11 GB · Amazon unmatched
ASUS ROG-POSEIDON-GTX1080TI-P11G-GAMING NVIDIA GeForce GTX 1080 Ti 11 GB GDDR5X
11 GB · Amazon unmatched
Sources
Model: official config google/gemma-2-9b-it (official-fallback-config). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: CPU_RAM_OFFLOAD_REQUIRED. Amazon: affiliate commerce match, not a spec source.