Can I Run Gemma 3 on NVIDIA GeForce RTX 3090?
Written by Jakub Rusinowski · Last updated July 12, 2026
Yes, comfortably — Gemma 3 27B Instruct at Q4_K_M needs 18.4 GB at 8K context (16.3 GB weights + 2.1 GB KV cache/overhead), leaving ~5.6 GB of the NVIDIA GeForce RTX 3090's 24 GB, at ~31 tok/s (est.), with room for up to 64K context.
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NVIDIA GeForce RTX 3090 Specs
| VRAM | 24 GB |
| Memory Bandwidth | 936 GB/s |
Gemma 3 27B Instruct on the NVIDIA GeForce RTX 3090: VRAM by quantization
| Quant | VRAM needed | Fits 24 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 56.1 GB | ✗ No | — | — |
| Q8_0 | 30.8 GB | ✗ No | — | — |
| Q6_K | 24.3 GB | ✗ No | — | — |
| Q5_K_M | 21.3 GB | ✓ Yes | 32K | — |
| Q4_K_M | 18.4 GB | ✓ Yes | 64K | — |
| Q3_K_M | 13.6 GB | ✓ Yes | 128K | — |
| Q2_K | 11 GB | ✓ Yes | 128K | — |
Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 24 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the NVIDIA GeForce RTX 3090: 8K 18.4 GB · 32K 20.4 GB · 128K 28.5 GB ✗. Past 128K it no longer fits 24 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Gemma 3 27B Instruct on 24 GB of system RAM, CPU only: runs comfortably.
Gemma 3 Sizes That Fit the NVIDIA GeForce RTX 3090 (at 8K context)
| Gemma 3 27B Instruct | Q4_K_M · 18.4 GB at 8K context · ~31 tok/s (est.) |
| Gemma 3 12B Instruct | Q4_K_M · 9.1 GB at 8K context · ~62 tok/s (est.) |
| Gemma 3 4B Instruct | Q4_K_M · 3.6 GB at 8K context · ~146 tok/s (est.) |
| Gemma 3 1B Instruct | Q4_K_M · 1.5 GB at 8K context · ~298 tok/s (est.) |
At 2 hrs/day, buying (~$1,499) beats renting at $0.34/hr after about 6.1 years.
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Gemma 3 on the NVIDIA GeForce RTX 3090 — does it fit?
Yes, comfortably — Gemma 3 27B Instruct at Q4_K_M needs 18.4 GB at 8K context (16.3 GB weights + 2.1 GB KV cache/overhead), leaving ~5.6 GB of the NVIDIA GeForce RTX 3090's 24 GB, at ~31 tok/s (est.), with room for up to 64K context.
Which Gemma 3 variant fits best on the NVIDIA GeForce RTX 3090?
Gemma 3 27B Instruct at Q4_K_M quantization needs 18.4 GB at 8K context (16.3 GB weights + 2.1 GB KV cache/overhead), estimated ~31 tokens/sec, up to 64K context.
Every Gemma 3 size on the NVIDIA GeForce RTX 3090
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Gemma 3 27B Instruct | 18.4 GB | Runs | ~31 tok/s |
| Gemma 3 12B Instruct | 9.1 GB | Runs | ~62 tok/s |
| Gemma 3 4B Instruct | 3.6 GB | Runs | ~146 tok/s |
| Gemma 3 1B Instruct | 1.5 GB | Runs | ~298 tok/s |
Gemma 3 on Other GPUs
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VRAM Tier
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