Can I Run Gemma 3 on NVIDIA GeForce RTX 4070 Super?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, but it's tight — Gemma 3 12B Instruct at Q4_K_M needs 11.1 GB at 8K context (7.2 GB weights + 3.9 GB KV cache/overhead), leaving ~0.9 GB of the NVIDIA GeForce RTX 4070 Super's 12 GB, at ~47 tok/s (est.), with room for up to 8K context.
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NVIDIA GeForce RTX 4070 Super Specs
| VRAM | 12 GB |
| Memory Bandwidth | 504 GB/s |
Gemma 3 12B Instruct on the NVIDIA GeForce RTX 4070 Super: VRAM by quantization
| Quant | VRAM needed | Fits 12 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 27.9 GB | ✗ No | — | — |
| Q8_0 | 16.6 GB | ✗ No | — | Build for this |
| Q6_K | 13.7 GB | ✗ No | — | — |
| Q5_K_M | 12.4 GB | ✗ No | — | Build for this |
| Q4_K_M | 11.1 GB | ✓ Yes | 8K | Build for this |
| Q3_K_M | 9 GB | ✓ Yes | 8K | — |
| Q2_K | 7.8 GB | ✓ Yes | 16K | — |
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 12 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 4070 Super: 8K 11.1 GB · 32K 20.4 GB ✗ · 128K 57.4 GB ✗. Past 32K it no longer fits 12 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Gemma 3 12B Instruct on 16 GB of system RAM, CPU only: runs, but it is tight.
Gemma 3 Sizes That Fit the NVIDIA GeForce RTX 4070 Super (at 8K context)
| Gemma 3 12B Instruct | Q4_K_M · 11.1 GB at 8K context · ~47 tok/s (est.) |
| Gemma 3 4B Instruct | Q4_K_M · 4.4 GB at 8K context · ~116 tok/s (est.) |
| Gemma 3 1B Instruct | Q4_K_M · 2 GB at 8K context · ~239 tok/s (est.) |
At 2 hrs/day, buying (~$599) beats renting at $0.34/hr after about 2.4 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
Does the NVIDIA GeForce RTX 4070 Super have enough VRAM for Gemma 3?
Yes, but it's tight — Gemma 3 12B Instruct at Q4_K_M needs 11.1 GB at 8K context (7.2 GB weights + 3.9 GB KV cache/overhead), leaving ~0.9 GB of the NVIDIA GeForce RTX 4070 Super's 12 GB, at ~47 tok/s (est.), with room for up to 8K context.
Which quantization of Gemma 3 should I use on the NVIDIA GeForce RTX 4070 Super?
Gemma 3 12B Instruct at Q4_K_M quantization needs 11.1 GB at 8K context (7.2 GB weights + 3.9 GB KV cache/overhead), estimated ~47 tokens/sec, up to 8K context.
Every Gemma 3 size on the NVIDIA GeForce RTX 4070 Super
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Gemma 3 27B Instruct | 25.4 GB | Does not fit | — |
| Gemma 3 12B Instruct | 11.1 GB | Runs | ~47 tok/s |
| Gemma 3 4B Instruct | 4.4 GB | Runs | ~116 tok/s |
| Gemma 3 1B Instruct | 2 GB | Runs | ~239 tok/s |
Gemma 3 on Other GPUs
- Gemma 3 on NVIDIA GeForce RTX 5070
- Gemma 3 on NVIDIA GeForce RTX 4070 Ti
- Gemma 3 on NVIDIA GeForce RTX 4070
- Gemma 3 on NVIDIA GeForce RTX 3060 (12GB)
- Gemma 3 on Intel Arc B580
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VRAM Tier
Troubleshooting
- CUDA out of memory — why it happens and how to fix it
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)
Buying Guide
← Can I Run It? | Gemma 3 Model Page | NVIDIA GeForce RTX 4070 Super GPU Page | VRAM calculator | Check Your Hardware