Can I Run Gemma 4 on NVIDIA GeForce RTX 3080 (10GB)?
Written by Jakub Rusinowski · Last updated July 12, 2026
Yes, but it's tight — Gemma 4 12B (Unified) at Q4_K_M needs 9.4 GB at 8K context (7.2 GB weights + 2.2 GB KV cache/overhead), leaving ~0.6 GB of the NVIDIA GeForce RTX 3080 (10GB)'s 10 GB, at ~53 tok/s (est.), with room for up to 8K context.
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NVIDIA GeForce RTX 3080 (10GB) Specs
| VRAM | 10 GB |
| Memory Bandwidth | 760 GB/s |
Gemma 4 12B (Unified) on the NVIDIA GeForce RTX 3080 (10GB): VRAM by quantization
| Quant | VRAM needed | Fits 10 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 26.1 GB | ✗ No | — | — |
| Q8_0 | 14.9 GB | ✗ No | — | — |
| Q6_K | 11.9 GB | ✗ No | — | — |
| Q5_K_M | 10.6 GB | ✗ No | — | — |
| Q4_K_M | 9.4 GB | ✓ Yes | 8K | — |
| Q3_K_M | 7.2 GB | ✓ Yes | 16K | — |
| Q2_K | 6.1 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 10 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 3080 (10GB): 8K 9.4 GB · 32K 13.3 GB ✗ · 125K 28.5 GB ✗. Past 32K it no longer fits 10 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? Gemma 4 12B (Unified) on 16 GB of system RAM, CPU only: runs, but it is tight.
Gemma 4 Sizes That Fit the NVIDIA GeForce RTX 3080 (10GB) (at 8K context)
| Gemma 4 12B (Unified) | Q4_K_M · 9.4 GB at 8K context · ~53 tok/s (est.) |
| Gemma 4 E4B | Q4 (QAT) · 6.4 GB at 8K context · ~77 tok/s (est.) |
| Gemma 4 E2B | Q4 (QAT) · 4.7 GB at 8K context · ~107 tok/s (est.) |
At 2 hrs/day, buying (~$699) beats renting at $0.34/hr after about 2.9 years.
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FAQ
Will Gemma 4 run on the NVIDIA GeForce RTX 3080 (10GB)?
Yes, but it's tight — Gemma 4 12B (Unified) at Q4_K_M needs 9.4 GB at 8K context (7.2 GB weights + 2.2 GB KV cache/overhead), leaving ~0.6 GB of the NVIDIA GeForce RTX 3080 (10GB)'s 10 GB, at ~53 tok/s (est.), with room for up to 8K context.
Which Gemma 4 variant fits best on the NVIDIA GeForce RTX 3080 (10GB)?
Gemma 4 12B (Unified) at Q4_K_M quantization needs 9.4 GB at 8K context (7.2 GB weights + 2.2 GB KV cache/overhead), estimated ~53 tokens/sec, up to 8K context.
Every Gemma 4 size on the NVIDIA GeForce RTX 3080 (10GB)
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Gemma 4 31B | 21.3 GB | Does not fit | — |
| Gemma 4 26B-A4B | 18.2 GB | Does not fit | — |
| Gemma 4 12B (Unified) | 9.4 GB | Runs | ~53 tok/s |
| Gemma 4 E4B | 6.4 GB | Runs | ~77 tok/s |
| Gemma 4 E2B | 4.7 GB | Runs | ~107 tok/s |
Gemma 4 on Other GPUs
- Gemma 4 on Intel Arc B570
- Gemma 4 on NVIDIA GeForce RTX 5070
- Gemma 4 on NVIDIA GeForce RTX 5060 Ti 8GB
- Gemma 4 on NVIDIA GeForce RTX 5060
- Gemma 4 on NVIDIA GeForce RTX 4070 Ti
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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
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