MODEL ARCHITECTURE SPEC • GOOGLE27.2B Dense
Google Gemma 2 27B Instruct VRAM & inference speed
27.2B Total ParamsDense Architecture46 Layers • 16 KV Heads8K Default Ctx (Max 8K)Ollama: gemma2:27b
Accurate memory requirements, KV cache footprint, and tokens/sec generation benchmarks for running Google Gemma 2 27B Instruct across local GPUs, Apple Silicon Macs, and cloud instances.
⚡ TIGHT FIT23.81 GB (99%)~32 t/s
Google Gemma 2 27B Instruct on AMD Radeon RX 7900 XTX (24GB GDDR6)
⚡ Tight Fit — Runs 100% on GPU (Low Headroom)
⚡ TIGHT FIT
Required VRAM
23.81 GB
99% of hardware capacity (24 GB)Est. Decode Speed
~32 tok/s
Dense model @ 960 GB/sAvailable Headroom
+0.19 GB
Tight margin — close background appsMemory Allocation & Headroom
23.81 GB allocated of 24 GB capacity
99% utilized
Weights: 16.32 GB
KV: (32K): 6.17 GB
Overhead: 1.32 GB
Free Headroom: +0.19 GB
⚡ Architecture & Throughput Transparency: Single-user decode speed (~32 tok/s) is memory-bandwidth bound at batch size = 1 on AMD Radeon RX 7900 XTX (24GB GDDR6) (960 GB/s). Prompt prefill / TTFT (~464 tok/s) is compute-bound and utilizes GPU Tensor cores. Actual latency varies with FlashAttention-2 and runtime engine (Ollama/vLLM/llama.cpp).
OLLAMA_FLASH_ATTENTION=1 OLLAMA_KV_CACHE_TYPE=q8_0 ollama run gemma2:27bCloud Instance Options for Google Gemma 2 27B Instruct
On-DemandDeploy this model on an on-demand cloud GPU without local hardware constraints or power usage:
RunPod Cloud GPUsBest 1-Click Ollama & vLLM
$0.34/hr (RTX 4070 Ti) – $2.39/hr (H100)Vast.ai GPU MarketplaceCheapest Dual RTX 3090 / 4090
$0.18/hr (RTX 3060) – $0.55/hr (RTX 4090)Lambda GPU CloudEnterprise 8x H100 Clusters
$1.99/hr (GH200 / H100)Quantization Precision Matrix
32K ctx • KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 54.4 GB | 6.17 GB | 63.22 GB (263%) | 0 t/s | OOM |
| Q8_08.5 bpw | 28.83 GB | 6.17 GB | 36.76 GB (153%) | 0 t/s | OOM |
| Q6_K6.56 bpw | 22.3 GB | 6.17 GB | 30 GB (125%) | ~5 t/s | PARTIAL |
| Q5_K_M5.68 bpw | 19.31 GB | 6.17 GB | 26.91 GB (112%) | ~6 t/s | PARTIAL |
| Q4_K_M4.8 bpw | 16.32 GB | 6.17 GB | 23.81 GB (99%) | ~32 t/s | FITS |
| FP44.25 bpw | 14.42 GB | 6.17 GB | 21.84 GB (91%) | ~36 t/s | FITS |
| IQ3_XS3.3 bpw | 11.15 GB | 6.17 GB | 18.46 GB (77%) | ~46 t/s | FITS |
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Hardware Compatibility Matrix for Google Gemma 2 27B Instruct
Standard Q4_K_M precision with 32K context window and Q8_0 KV cache
| Hardware System | VRAM Envelope | Required VRAM | Headroom | Est. Decode Speed | Compatibility | Test Fit |
|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 5090 (32GB GDDR7) Consumer GPU • 1792 GB/s | 32 GB | 23.81 GB | +8.19 GB | ~70 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 4090 (24GB GDDR6X) Consumer GPU • 1008 GB/s | 24 GB | 23.81 GB | +0.19 GB | ~40 tok/s | ⚡ TIGHT FIT | Test Fit → |
| 2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM) Multi-GPU Rig • 936 GB/s | 48 GB | 23.81 GB | +24.19 GB | ~34 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 5080 (16GB GDDR7) Consumer GPU • 960 GB/s | 16 GB | 23.81 GB | -7.81 GB | 0 (OOM) | ✕ OOM | Test Fit → |
| NVIDIA RTX 4070 Ti Super (16GB) Consumer GPU • 672 GB/s | 16 GB | 23.81 GB | -7.81 GB | 0 (OOM) | ✕ OOM | Test Fit → |
| NVIDIA GeForce RTX 3060 (12GB) Consumer GPU • 360 GB/s | 12 GB | 23.81 GB | -11.81 GB | 0 (OOM) | ✕ OOM | Test Fit → |
| Apple Mac Mini M4 Pro (64GB Unified Memory) Apple Silicon • 273 GB/s | 54 GB | 23.81 GB | +30.19 GB | ~10 tok/s | ✓ FITS | Test Fit → |
| Apple Mac Studio M4 Max (128GB Unified Memory) Apple Silicon • 546 GB/s | 112 GB | 23.81 GB | +88.19 GB | ~20 tok/s | ✓ FITS | Test Fit → |
| Apple Mac Studio M5 Ultra (256GB Unified Memory) Apple Silicon • 890 GB/s | 236 GB | 23.81 GB | +212.19 GB | ~33 tok/s | ✓ FITS | Test Fit → |
| AMD Strix Halo Mini-PC (Ryzen AI Max+ 395 128GB) Unified APU / Mini-PC • 256 GB/s | 110 GB | 23.81 GB | +86.19 GB | ~8 tok/s | ✓ FITS | Test Fit → |
| NVIDIA DGX Spark (128GB Grace-Blackwell Unified) AI Appliance • 273 GB/s | 118 GB | 23.81 GB | +94.19 GB | ~11 tok/s | ✓ FITS | Test Fit → |
| NVIDIA H100 SXM (80GB HBM3 Cloud GPU) Datacenter Cloud GPU • 3350 GB/s | 80 GB | 23.81 GB | +56.19 GB | ~139 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 5070 Ti (16GB GDDR7) Consumer GPU • 896 GB/s | 16 GB | 23.81 GB | -7.81 GB | 0 (OOM) | ✕ OOM | Test Fit → |
| NVIDIA GeForce RTX 5070 (12GB GDDR7) Consumer GPU • 672 GB/s | 12 GB | 23.81 GB | -11.81 GB | 0 (OOM) | ✕ OOM | Test Fit → |
| NVIDIA GeForce RTX 4080 Super (16GB GDDR6X) Consumer GPU • 736 GB/s | 16 GB | 23.81 GB | -7.81 GB | 0 (OOM) | ✕ OOM | Test Fit → |
| AMD Radeon RX 7900 XTX (24GB GDDR6) Consumer GPU • 960 GB/s | 24 GB | 23.81 GB | +0.19 GB | ~32 tok/s | ⚡ TIGHT FIT | Test Fit → |
| AMD Radeon RX 7900 XT (20GB GDDR6) Consumer GPU • 800 GB/s | 20 GB | 23.81 GB | -3.81 GB | ~6 tok/s | ⚡ PARTIAL | Test Fit → |
| Apple Mac Studio M2 Ultra (192GB Unified Memory) Apple Silicon Workstation • 800 GB/s | 144 GB | 23.81 GB | +120.19 GB | ~30 tok/s | ✓ FITS | Test Fit → |