Can I Run Gemma 3n on NVIDIA GeForce RTX 3070 Ti?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, comfortably — Gemma 3n E4B at Q4_K_M needs 6.7 GB at 8K context (4.7 GB weights + 2 GB KV cache/overhead), leaving ~1.3 GB of the NVIDIA GeForce RTX 3070 Ti's 8 GB, at ~101 tok/s (est.), with room for up to 16K context.
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NVIDIA GeForce RTX 3070 Ti Specs
| VRAM | 8 GB |
| Memory Bandwidth | 608 GB/s |
Gemma 3n E4B on the NVIDIA GeForce RTX 3070 Ti: VRAM by quantization
| Quant | VRAM needed | Fits 8 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 17.6 GB | ✗ No | — | — |
| Q8_0 | 10.3 GB | ✗ No | — | — |
| Q6_K | 8.4 GB | ✗ No | — | — |
| Q5_K_M | 7.5 GB | ✓ Yes | 8K | — |
| Q4_K_M | 6.7 GB | ✓ Yes | 16K | — |
| Q3_K_M | 5.3 GB | ✓ Yes | 16K | — |
| Q2_K | 4.5 GB | ✓ Yes | 32K | — |
Assumes an 8K-token context with an f16 KV cache, on an estimated architecture — this model publishes no config we can read. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 8 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 3070 Ti: 8K 6.7 GB · 32K 10.1 GB ✗. Past 32K it no longer fits 8 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Gemma 3n E4B on 16 GB of system RAM, CPU only: runs.
Gemma 3n Sizes That Fit the NVIDIA GeForce RTX 3070 Ti (at 8K context)
| Gemma 3n E4B | Q4_K_M · 6.7 GB at 8K context · ~101 tok/s (est.) |
| Gemma 3n E2B | Q4_K_M · 5.1 GB at 8K context · ~151 tok/s (est.) |
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FAQ
Is the NVIDIA GeForce RTX 3070 Ti enough to run Gemma 3n locally?
Yes, comfortably — Gemma 3n E4B at Q4_K_M needs 6.7 GB at 8K context (4.7 GB weights + 2 GB KV cache/overhead), leaving ~1.3 GB of the NVIDIA GeForce RTX 3070 Ti's 8 GB, at ~101 tok/s (est.), with room for up to 16K context.
What's the best Gemma 3n size for the NVIDIA GeForce RTX 3070 Ti?
Gemma 3n E4B at Q4_K_M quantization needs 6.7 GB at 8K context (4.7 GB weights + 2 GB KV cache/overhead), estimated ~101 tokens/sec, up to 16K context.
Every Gemma 3n size on the NVIDIA GeForce RTX 3070 Ti
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Gemma 3n E4B | 6.7 GB | Runs | ~101 tok/s |
| Gemma 3n E2B | 5.1 GB | Runs | ~151 tok/s |
Gemma 3n on Other GPUs
- Gemma 3n on NVIDIA GeForce RTX 5060 Ti 8GB
- Gemma 3n on NVIDIA GeForce RTX 5060
- Gemma 3n on NVIDIA GeForce RTX 4060
- Gemma 3n on NVIDIA GeForce RTX 3070
- Gemma 3n on AMD Radeon RX 9060 XT 8GB
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