Can I Run Gemma 3 on NVIDIA GeForce RTX 5090?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 29 września 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 ~13.6 GB of the NVIDIA GeForce RTX 5090's 32 GB, at ~74 tok/s (est.), with room for up to 128K context.
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NVIDIA GeForce RTX 5090 Specs
| VRAM | 32 GB |
| Memory Bandwidth | 1792 GB/s |
Gemma 3 27B Instruct on the NVIDIA GeForce RTX 5090: VRAM by quantization
| Quant | VRAM needed | Fits 32 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 56.1 GB | ✗ No | — | — |
| Q8_0 | 30.8 GB | ✓ Yes | 16K | — |
| Q6_K | 24.3 GB | ✓ Yes | 64K | — |
| Q5_K_M | 21.3 GB | ✓ Yes | 128K | — |
| Q4_K_M | 18.4 GB | ✓ Yes | 128K | — |
| 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 32 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 5090: 8K 18.4 GB · 32K 20.4 GB · 128K 28.5 GB. Every window this model publishes still fits 32 GB.
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 5090 (at 8K context)
| Gemma 3 27B Instruct | Q4_K_M · 18.4 GB at 8K context · ~74 tok/s (est.) |
| Gemma 3 12B Instruct | Q4_K_M · 9.1 GB at 8K context · ~133 tok/s (est.) |
| Gemma 3 4B Instruct | Q4_K_M · 3.6 GB at 8K context · ~250 tok/s (est.) |
| Gemma 3 1B Instruct | Q4_K_M · 1.5 GB at 8K context · ~375 tok/s (est.) |
At 2 hrs/day, buying (~$1,999) beats renting at $0.34/hr after about 8.2 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 5090 — 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 ~13.6 GB of the NVIDIA GeForce RTX 5090's 32 GB, at ~74 tok/s (est.), with room for up to 128K context.
Which Gemma 3 variant fits best on the NVIDIA GeForce RTX 5090?
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 ~74 tokens/sec, up to 128K context.
Every Gemma 3 size on the NVIDIA GeForce RTX 5090
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Gemma 3 27B Instruct | 18.4 GB | Runs | ~74 tok/s |
| Gemma 3 12B Instruct | 9.1 GB | Runs | ~133 tok/s |
| Gemma 3 4B Instruct | 3.6 GB | Runs | ~250 tok/s |
| Gemma 3 1B Instruct | 1.5 GB | Runs | ~375 tok/s |
Gemma 3 on Other GPUs
- Gemma 3 on Apple M4
- Gemma 3 on Apple M2 Pro
- Gemma 3 on Apple M1 Pro
- Gemma 3 on Apple M5
- Gemma 3 on Apple M3 Pro
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VRAM Tier
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