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Can you run Gemma 3 27B locally?

Gemma 3 family · March 2025 · 27.4B parameters · Hugging Face model card

Gemma 3 27B runs locally on a 24 GB GPU at Q4_K_M, which needs about 20.2 GB of VRAM with a 4k-token context. A 32 GB or larger GPU is needed for comfortable 32k-token use, because the upper-bound KV cache grows to 16.6 GB at 32k tokens.

Minimum: 24 GB VRAM GPU (RTX 3090, RTX 4090) at Q4_K_M, 4k context  ·  Recommended: 32 GB+ VRAM (RTX PRO 6000 Blackwell 96GB or 2× 24GB) at Q5_K_M+ for long contexts

Parameters (total)
27.4B
VRAM at Q4_K_M (4k ctx)
20.2 GB
Context window
131,072 tokens
Architecture source
HF config.json (verified)

How much VRAM does Gemma 3 27B need at each quantization?

Gemma 3 27B needs 20.2 GB of VRAM at Q4_K_M. The table below lists weights-only size and total VRAM including overhead for each common quantization level with 4k and 32k token contexts.

QuantizationBits / weightWeights onlyTotal + KV @4k ctxTotal + KV @32k ctx
Q4_K_M 4.8 16.4 GB 20.2 GB 34.7 GB
Q5_K_M 5.7 19.5 GB 23.6 GB 38.1 GB
Q6_K 6.6 22.6 GB 27.0 GB 41.5 GB
Q8_0 8.5 29.1 GB 34.1 GB 48.7 GB
FP16 16 54.8 GB 62.4 GB 76.9 GB

Gemma 3 uses a 1024-token sliding attention window on 5 of every 6 layers; the table shows the conservative full-attention upper bound, so real long-context use is slightly lower.

Method: weights = parameters × bits-per-weight (Q4_K_M ≈ 4.8, Q5_K_M ≈ 5.7, Q6_K ≈ 6.6, Q8_0 ≈ 8.5, FP16 = 16), plus 10% loading overhead, plus KV cache from the verified architecture config (62 layers, 16 KV heads, 128 head dim). Source: Params 27.4B, 62 layers, 16 KV heads, head dim 128, 131072 context, sliding window 1024 — HF config.json (unsloth/gemma-3-27b-it mirror of google/gemma-3-27b-it).

Which GPUs can run Gemma 3 27B locally?

At Q4_K_M with a 4k context, Gemma 3 27B needs 20.2 GB of VRAM. The lists below are computed live from our GPU database and grouped by how much headroom the card has. Disclosure: CompareAIHardware.com participates in the Amazon Associates program and earns from qualifying purchases through links on this page. Affiliate relationships do not influence our recommendations.

Runs Gemma 3 27B comfortably (25%+ VRAM headroom)

GPUVRAMBandwidthType
AMD Radeon Pro W7800 32 GB 576 GB/s Pro GPU Check price
GeForce RTX 5090 Can it run? 32 GB 1792 GB/s Consumer GPU Check price
NVIDIA RTX 5000 Ada 32 GB 576 GB/s Pro GPU Check price
NVIDIA RTX PRO 4500 Blackwell 32 GB 896 GB/s Pro GPU Check price
NVIDIA A100 40GB SXMEOL 40 GB 1555 GB/s Data Center GPU
AMD Radeon Pro W7900 48 GB 864 GB/s Pro GPU Check price
NVIDIA RTX PRO 5000 Blackwell 48 GB 1344 GB/s Pro GPU
RTX 6000 Ada 48 GB 960 GB/s Pro GPU Check price
RTX A6000 48 GB 768 GB/s Pro GPU Check price
H100 SXM 80 GB 3350 GB/s Data Center GPU
NVIDIA A100 80GB SXM 80 GB 2039 GB/s Data Center GPU
NVIDIA H100 PCIe 80GB 80 GB 2039 GB/s Data Center GPU
NVIDIA RTX PRO 6000 Blackwell 96 GB 1792 GB/s Pro GPU Check price
H200 SXM 141 GB 4800 GB/s Data Center GPU
AMD Instinct MI300X 192 GB 5300 GB/s Data Center GPU
NVIDIA B200 192 GB 8000 GB/s Data Center GPU
AMD Instinct MI325X 256 GB 6000 GB/s Data Center GPU
AMD Instinct MI350X 288 GB 8000 GB/s Data Center GPU
AMD Instinct MI355X 288 GB 8000 GB/s Data Center GPU
NVIDIA B300 (Blackwell Ultra) 288 GB 8000 GB/s Data Center GPU
AMD Instinct MI430X 432 GB 23300 GB/s Data Center GPU
AMD Instinct MI455X 432 GB 23300 GB/s Data Center GPU

Minimum GPUs that fit Gemma 3 27B at Q4_K_M

These GPUs hold the model but leave little headroom — keep contexts short.

GPUVRAMBandwidthType
GeForce RTX 3090EOL Can it run? 24 GB 936 GB/s Consumer GPU Check price
GeForce RTX 3090 TiEOL 24 GB 1008 GB/s Consumer GPU Check price
GeForce RTX 4090 Can it run? 24 GB 1008 GB/s Consumer GPU Check price
NVIDIA RTX PRO 4000 Blackwell 24 GB 672 GB/s Pro GPU Check price
Radeon RX 7900 XTX 24 GB 960 GB/s Consumer GPU Check price

Needs 2+ GPUs to run Gemma 3 27B

One of these cards is too small on its own, but a pair (tensor or pipeline parallel, ~90% efficiency) covers the 20.2 GB requirement. See our multi-GPU guide for setup.

GPUVRAMBandwidthType
Arc B580 12 GB ×2 456 GB/s Consumer GPU Check price
GeForce RTX 3060 12GB 12 GB ×2 360 GB/s Consumer GPU Check price
GeForce RTX 3080 TiEOL 12 GB ×2 912 GB/s Consumer GPU Check price
GeForce RTX 4070EOL 12 GB ×2 504 GB/s Consumer GPU Check price
GeForce RTX 4070 SUPEREOL 12 GB ×2 504 GB/s Consumer GPU Check price
GeForce RTX 5070 12 GB ×2 672 GB/s Consumer GPU Check price
Radeon RX 7700 XT 12 GB ×2 432 GB/s Consumer GPU Check price
Radeon RX 9070 GRE 12 GB ×2 432 GB/s Consumer GPU
Arc A770 16GB 16 GB ×2 560 GB/s Consumer GPU Check price
GeForce RTX 4060 Ti 16GB 16 GB ×2 288 GB/s Consumer GPU Check price
GeForce RTX 4070 Ti SUPEREOL 16 GB ×2 672 GB/s Consumer GPU Check price
GeForce RTX 4080EOL 16 GB ×2 716 GB/s Consumer GPU Check price
GeForce RTX 4080 SUPER 16 GB ×2 736 GB/s Consumer GPU Check price
GeForce RTX 5060 Ti 16GB 16 GB ×2 448 GB/s Consumer GPU Check price
GeForce RTX 5070 Ti 16 GB ×2 896 GB/s Consumer GPU Check price
GeForce RTX 5080 16 GB ×2 960 GB/s Consumer GPU Check price
NVIDIA RTX PRO 2000 Blackwell 16 GB ×2 288 GB/s Pro GPU Check price
Radeon RX 6800 XTEOL 16 GB ×2 512 GB/s Consumer GPU Check price
Radeon RX 7600 XT 16 GB ×2 288 GB/s Consumer GPU Check price
Radeon RX 7800 XT 16 GB ×2 624 GB/s Consumer GPU Check price
Radeon RX 9060 XT 16GB 16 GB ×2 320 GB/s Consumer GPU
Radeon RX 9060 XT LP (16GB) 16 GB ×2 320 GB/s Consumer GPU
Radeon RX 9070 16 GB ×2 640 GB/s Consumer GPU Check price
Radeon RX 9070 XT 16 GB ×2 640 GB/s Consumer GPU Check price
Radeon RX 7900 XT 20 GB ×2 800 GB/s Consumer GPU Check price

Can a Mac run Gemma 3 27B?

Yes — these Apple Silicon machines fit Gemma 3 27B at Q4_K_M, since macOS lets the GPU use about 75% of unified memory. Generation speed is bound by memory bandwidth, so the GB/s column matters as much as capacity.

Apple SiliconUnified memoryUsable by GPU (~75%)Bandwidth
Apple M4 32 GB 24 GB 120 GB/s
M6 (Mac mini) 32 GB 24 GB 170 GB/s
Apple M3 Pro 36 GB 27 GB 300 GB/s
Apple M4 Pro 64 GB 48 GB 273 GB/s
Apple M5 Pro 64 GB 48 GB 307 GB/s
M5 Pro (Mac mini) 64 GB 48 GB 307 GB/s
Apple M3 Max 128 GB 96 GB 400 GB/s
Apple M5 Max 128 GB 96 GB 614 GB/s
M4 Max (MacBook Pro) 128 GB 96 GB 546 GB/s
M5 Max (Mac Studio) 128 GB 96 GB —
M5 Ultra (Mac Studio) 512 GB 384 GB 1200 GB/s

Can Gemma 3 27B run on mini PCs, Jetson, or NPU devices?

These edge and NPU devices from our database have enough memory for Gemma 3 27B at Q4_K_M. Their memory bandwidth is far below discrete GPUs, so expect a fraction of desktop generation speed.

DeviceMemoryBandwidthType
Intel Core Ultra 9 288V (Lunar Lake) 32 GB 136 GB/s NPU Chip
Jetson AGX Orin 32GB 32 GB 204 GB/s Edge Compute Device
Jetson AGX Orin 64GB 64 GB 204 GB/s Edge Compute Device
Snapdragon X Elite (X1E-84-100) 64 GB 135 GB/s NPU Chip
AMD Ryzen AI 9 HX 370 (Strix Point) 96 GB 120 GB/s NPU Chip
NVIDIA RTX Spark (superchip) 128 GB — NPU Chip

Which pre-built systems can run Gemma 3 27B?

These mini PCs and workstations from our database fit Gemma 3 27B at Q4_K_M. Usable-memory figures are conservative: Windows shares about half of system RAM with the GPU by default (Linux can expose more), macOS lets Apple Silicon GPUs use about 75% of unified memory, and Linux unified-memory systems such as GB10 expose roughly 90%. Generation speed is bound by memory bandwidth, so compare the GB/s column before buying.

SystemTypeMemoryUsable for AIBandwidthGPUs
Mac mini M4 Pro Mini PC 48 GB 24 GB 273 GB/s —
Mac Studio M5 Max (36 GB) Workstation 36 GB 27 GB 460 GB/s 1
ASRock DeskMeet X600 (Ryzen 7 7600) Mini PC 64 GB 32 GB 83 GB/s —
BIZON G3000 G2 (1x RTX 5090) Workstation 32 GB 32 GB 1792 GB/s 1
Beelink SER9 Pro (Ryzen AI 9 HX 370, 64GB) Mini PC 64 GB 32 GB 120 GB/s —
Custom RTX 5090 AI Workstation (Value Build) Workstation 32 GB 32 GB 1792 GB/s 1
HP Elite Mini 800 G9 (Core i7-13700T) Mini PC 64 GB 32 GB 83 GB/s —
HP OMEN 45L RTX 5090 Desktop Workstation 32 GB 32 GB — 1
Intel NUC 13 Pro (Core i7-1360P) Mini PC 64 GB 32 GB 83 GB/s —
MinisForum UM780 XTX (Ryzen 7 7840HS) Mini PC 64 GB 32 GB 89 GB/s —
MinisForum UM890 Pro (Ryzen 9 8945HS) Mini PC 64 GB 32 GB 89 GB/s —
Puget Systems Datum (1x RTX 5090) Workstation 32 GB 32 GB 1792 GB/s 1
Sentinel RTX 5090 Tower Workstation Workstation 32 GB 32 GB — 1
ASRock NUC BOX-255H (Core Ultra 7 255H) Mini PC 96 GB 48 GB 102 GB/s —
Apple Mac Studio M2 Ultra (64GB) Workstation 64 GB 48 GB 800 GB/s 1
Custom Dual RTX 4090 Training Workstation Workstation 48 GB 48 GB 1008 GB/s 2
Dell Precision 7960 Tower (1x RTX 6000 Ada) Workstation 48 GB 48 GB 960 GB/s 1
HP Z8 Fury G5 (1x RTX 6000 Ada) Workstation 48 GB 48 GB 960 GB/s 1
ACEMAGIC F9A (Ryzen AI Max+ 395) Mini PC 128 GB 64 GB 256 GB/s —
AMD Ryzen AI Halo Developer Platform (Max+ 395) Mini PC 128 GB 64 GB 256 GB/s —
ArsenalPC MES2X Dual RTX 5090 AI Workstation Workstation 64 GB 64 GB — 2
BOSGAME M5 AI Mini Desktop (Ryzen AI Max+ 395) Mini PC 128 GB 64 GB — —
Chuwi UniBox AI395 (Ryzen AI Max+ 395) Mini PC 128 GB 64 GB 256 GB/s —
GMKtec EVO-X2 (Ryzen AI Max+ 395) Mini PC 128 GB 64 GB 256 GB/s —
MSI EdgeMesa N AI+ (RTX Spark N1X) Mini PC 128 GB 64 GB — —
MinisForum MS-S1 MAX (Ryzen AI Max+ 395) Mini PC 128 GB 64 GB 256 GB/s —
ACEMAGIC F9A (Ryzen AI Max+ PRO 495) Mini PC 192 GB 96 GB — —
BOXX APEXX 8R (1x RTX PRO 6000 Blackwell) Workstation 96 GB 96 GB 1792 GB/s 1
Chuwi UniBox AI495 Pro (Ryzen AI Max+ PRO 495) Mini PC 192 GB 96 GB 273 GB/s —
GEEKOM A9 Mega AI Workstation Workstation 128 GB 96 GB — 1
GMKtec EVO-X5 Pro (Ryzen AI Max+ PRO 495) Mini PC 192 GB 96 GB — —
NOVATECH RTX PRO 6000 AI Workstation Workstation 96 GB 96 GB — 1
System76 Thelio Major (1x RTX PRO 6000 Blackwell) Workstation 96 GB 96 GB 1792 GB/s 1
System76 Thelio Major (2x RTX 6000 Ada) Workstation 96 GB 96 GB 960 GB/s 2
Lenovo ThinkStation PGX Workstation 128 GB 115.2 GB 273 GB/s 1
NVIDIA DGX Spark Workstation 128 GB 115.2 GB 273 GB/s 1
BIZON G3000 G2 (4x RTX 5090) Workstation 128 GB 128 GB 1792 GB/s 4
Apple Mac Studio M2 Ultra (192GB) Workstation 192 GB 144 GB 800 GB/s 1
HP Z8 Fury G5 (4x RTX 6000 Ada) Workstation 192 GB 192 GB 960 GB/s 4

Frequently asked questions

How large is the Gemma 3 27B Q4_K_M file on disk?

The gguf Q4_K_M artifact is 16.55 GB on disk (ai_model_artifacts.size_bytes, bartowski/google_gemma-3-27b-it-GGUF). That is a download size, not runtime VRAM. Calculated runtime VRAM at Q4_K_M with 4K context is 20.16 GB (ModelFitService weights + 10% overhead + KV cache).

How much calculated VRAM does Gemma 3 27B need on a 24 GB GPU?

Calculated VRAM is 20.16 GB at Q4_K_M with 4K context versus 24 GB vendor_spec VRAM on GeForce RTX 4090 (products.specifications.vram_gb). Headroom is 3.84 GB. No tokens-per-second figure is shown: no exact product x model benchmark row.

Can an RTX 4090 run Gemma 3 27B?

Yes. Gemma 3 27B needs about 20.2 GB of VRAM at Q4_K_M with a 4k context, which fits the RTX 4090’s 24 GB with headroom for longer contexts thanks to Gemma 3’s sliding-window attention on most layers.

How much VRAM does Gemma 3 27B need?

Gemma 3 27B needs about 20.2 GB of VRAM at Q4_K_M with a 4k context and up to about 34.7 GB at 32k tokens using the full-attention upper bound; sliding-window attention keeps actual usage lower.

Is Gemma 3 27B multimodal?

Yes. The Gemma 3 27B instruction-tuned model processes images and text according to Google’s model card, so add roughly 0.4B vision-encoder parameters and keep extra VRAM headroom when using image input locally.

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