Can I run Gemma 3 12B on the GeForce RTX 5060 Ti 16GB?
Runs greatQ4_K_M fits in VRAM with 7.0 GB to spare: Runs great, est. 40.0 tok/s (35.2–44.8, calibrated estimate ±12%).
16 GB VRAM · 448.0 GB/s · FP16 23.7 TFLOPS. Assumes 32 GB of DDR5-5600 system RAM, Windows with this GPU driving the display, 8k context and an f16 KV cache.
Every quant of Gemma 3 12B on the GeForce RTX 5060 Ti 16GB
| Quant | File size | Verdict | Speed | Memory | Runs as | Notes |
|---|---|---|---|---|---|---|
| Q2_K | 4.77 GB | Runs great | est. 59.1 tok/s52.0–66.2calibrated estimate ±12% | 6.5 / 16.0 GB | Full GPU | — |
| IQ4_XS | 6.55 GB | Runs great | est. 44.3 tok/s38.9–49.6calibrated estimate ±12% | 8.3 / 16.0 GB | Full GPU | — |
| Q4_K_Mbaseline | 7.30 GB | Runs great | est. 40.0 tok/s35.2–44.8calibrated estimate ±12% | 9.0 / 16.0 GB | Full GPU | — |
| Q8_0 | 12.51 GB | Runs great | est. 24.0 tok/s21.2–26.9calibrated estimate ±12% | 14.2 / 16.0 GB | Full GPU | — |
Where the memory goes at Q4_K_M
- Weights
- 7.3 GB
- KV cache
- 0.5 GB
- Compute buffer
- 0.6 GB
- OS reserve
- 0.6 GB
- Free
- 7.0 GB
Context length vs. KV cache
| Context | KV f16 | KV q8_0 | KV q4_0 |
|---|---|---|---|
| 4k | 8.1 GBRuns great est. 41.4 tok/s36.5–46.4calibrated estimate ±12% | 8.0 GBRuns great est. 42.1 tok/s37.1–47.2calibrated estimate ±12% | 7.9 GBRuns great est. 42.5 tok/s37.4–47.6calibrated estimate ±12% |
| 8k | 8.4 GBRuns great est. 40.0 tok/s35.2–44.8calibrated estimate ±12% | 8.2 GBRuns great est. 41.3 tok/s36.4–46.3calibrated estimate ±12% | 8.0 GBRuns great est. 42.1 tok/s37.0–47.1calibrated estimate ±12% |
| 16k | 9.0 GBRuns great est. 37.5 tok/s33.0–41.9calibrated estimate ±12% | 8.5 GBRuns great est. 39.8 tok/s35.0–44.6calibrated estimate ±12% | 8.3 GBRuns great est. 41.2 tok/s36.3–46.2calibrated estimate ±12% |
| 32k | 10.2 GBRuns great est. 33.2 tok/s29.2–37.2calibrated estimate ±12% | 9.2 GBRuns great est. 37.1 tok/s32.7–41.6calibrated estimate ±12% | 8.7 GBRuns great est. 39.6 tok/s34.9–44.4calibrated estimate ±12% |
| 64k | 12.7 GBRuns great est. 27.0 tok/s23.8–30.3calibrated estimate ±12% | 10.7 GBRuns great est. 32.7 tok/s28.8–36.6calibrated estimate ±12% | 9.6 GBRuns great est. 36.8 tok/s32.4–41.2calibrated estimate ±12% |
| 128k | 17.6 GBRuns slowly est. 7.0 tok/s5.6–8.5calibrated estimate ±20% | 13.6 GBRuns great est. 26.4 tok/s23.2–29.5calibrated estimate ±12% | 11.4 GBRuns great est. 32.2 tok/s28.3–36.0calibrated estimate ±12% |
S = Runs great · A = Runs well · B = Runs slowly · F = Won't run
At Q4_K_M the verdict stays Runs great up to 64k context with an f16 KV cache, and up to 128k with q8_0.
Estimated speed
- Generation
- est. 40.0 tok/s (35.2–44.8, calibrated estimate ±12%)
- Prompt processing
- about 3,318 tok/s (1,991–4,645, rough estimate ±40%)
Measured on this exact combination
No public measurement for this exact combination yet; the numbers above are estimates.
If this is not enough
A larger model that also runs well on the GeForce RTX 5060 Ti 16GB
Runs wellQwen3.5 35B-A3B: Runs well, est. 20.4 tok/s (14.3–26.5, theoretical estimate ±30%)
A larger quant that still runs great
Runs greatQ8_0 (12.51 GB): Runs great, est. 24.0 tok/s (21.2–26.9, calibrated estimate ±12%)
How to run it
Commands for the Q4_K_M file. Both tools download from Hugging Face on first run.
File: google_gemma-3-12b-it-Q4_K_M.gguf (7.30 GB) from bartowski/google_gemma-3-12b-it-GGUF.
llama-server -hf bartowski/google_gemma-3-12b-it-GGUF:Q4_K_M -c 8192 -ngl all -fa on- -ngl all loads every layer on the GPU.
- -fa on enables flash attention (needed for KV cache quantization).
- --cache-type-k q8_0 --cache-type-v q8_0 shrinks the KV cache to 0.29 GB at 8k context.
PowerShell (quit the Ollama tray app first):
$env:OLLAMA_CONTEXT_LENGTH="8192"; ollama serve
ollama run hf.co/bartowski/google_gemma-3-12b-it-GGUF:Q4_K_M- Ollama defaults to 4k context on GPUs under 24 GB. Set OLLAMA_CONTEXT_LENGTH when starting the server, or /set parameter num_ctx inside the chat.
/set parameter num_ctx 8192
Related pages
Guide: How much VRAM do local LLMs need? 8–32 GB tiers (2026)
Other models on the GeForce RTX 5060 Ti 16GB
Gemma 3 12B on other hardware
Frequently asked questions
Can I run Gemma 3 12B on the GeForce RTX 5060 Ti 16GB?
Q4_K_M fits in VRAM with 7.0 GB to spare: Runs great, est. 40.0 tok/s (35.2–44.8, calibrated estimate ±12%). Q4_K_M needs 8.4 GB at 8k context; this setup has 15.4 GB of usable memory and 28.0 GB of free system RAM.
How much context can Gemma 3 12B use on the GeForce RTX 5060 Ti 16GB?
At Q4_K_M the verdict stays Runs great up to 64k context with an f16 KV cache (4.3 GB of KV) and up to 128k with a q8_0 KV cache (4.6 GB). The model supports up to 128k.
Which quant should I use, and how fast is it?
Q4_K_M (7.30 GB) is the recommended balance: Runs great, est. 40.0 tok/s (35.2–44.8, calibrated estimate ±12%). The largest tracked file that still gets Runs great is Q8_0 (12.51 GB), est. 24.0 tok/s (21.2–26.9, calibrated estimate ±12%).
Speeds are estimates from memory bandwidth, calibrated against public benchmarks, and each one comes with an error band and a confidence label. Real results vary with drivers, backend, context length and thermals.