GeForce RTX 5060 Ti
GeForce RTX 5060 Ti has 16 GB of VRAM at 448 GB/s — about 14.88 GiB usable after driver and compositor overhead. 1673 of 2118 indexed models fit at 128K context with q4_0 KV.
What fits at 128K context
| Model | Best quant | Params | Weights● | KV● | Total in memory◐ | Headroom◐ | tok/s◐ |
|---|---|---|---|---|---|---|---|
| gemma-3-12b-it-ultra-uncensored-heretic | Q8_0 | 12.2B | 11.65 GiB | 2.38 GiB | 14.88 GiB | 0.00 GiB | 23±12.9% |
| gemma-3-12b-it-vl-Deepseek-v3.1-Heretic-Uncensored-Thinking | Q8_0 | 12.2B | 11.65 GiB | 2.38 GiB | 14.88 GiB | 0.00 GiB | 23±12.9% |
| Floppa-12B-Gemma3-Uncensored | Q8_0 | 12.2B | 11.65 GiB | 2.38 GiB | 14.88 GiB | 0.00 GiB | 23±12.9% |
| gemma-3-12b-it-heretic | Q8_0 | 12.2B | 11.65 GiB | 2.38 GiB | 14.88 GiB | 0.00 GiB | 23±12.9% |
| gemma-3-12b-it-abliterated | Q8_0 | 12.2B | 11.65 GiB | 2.38 GiB | 14.88 GiB | 0.00 GiB | 23±12.9% |
| gemma-3-12b-it-abliterated-v2 | Q8_0 | 11.8B | 11.65 GiB | 2.38 GiB | 14.88 GiB | 0.00 GiB | 23±12.9% |
| gemma-3-12b-it | Q8_0 | 12.2B | 11.65 GiB | 2.38 GiB | 14.88 GiB | 0.00 GiB | 23±12.9% |
| GRM-2.6-Plus-0628 | IQ3_XXS | 27.8B | 11.76 GiB | 2.25 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| ThinkingCap-Qwen3.6-27B | IQ3_XXS | 27.4B | 11.76 GiB | 2.25 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Tess-4-27B | IQ3_XXS | 27.8B | 11.76 GiB | 2.25 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| NousCoder-14B | Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| spoomplesmaxx-mini-14B | I1-Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| vanilla-cn-roleplay-0.2 | I1-Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Claria-14b | I1-Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| qwen3-14b-code-reasoning-conversational | Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| NTX-2.1-Pro | I1-Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Qwen3-14B-Uncensored | I1-Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Qwen3-14B-Claude-4.5-Opus-High-Reasoning-Distill | Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Qwen3-14B | Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| FrogMini-14B-2510 | I1-Q4_K_M | — | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Qwen3-14B-abliterated | Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Josiefied-Qwen3-14B-abliterated-v3 | Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Hermes-4-14B | Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Slava-Qwen3-14B-Serbian | I1-Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Qwen3-14B-Base | Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Huihui-Qwen3-14B-abliterated-v2 | I1-Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Qwen3-14B-Instruct | Q4_K_M | 14.8B | 8.38 GiB | 5.63 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Phi-3-medium-128k-instruct | Q3_K_L | 14.0B | 6.98 GiB | 7.03 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Phi-3-medium-4k-instruct | I1-Q3_K_L | 14.0B | 6.98 GiB | 7.03 GiB | 14.87 GiB | 0.01 GiB | 23±12.9% |
| Pantheon-Reasoning-26B-A4B-1.1MoE | Q3_K_L | 26.5B | 12.59 GiB | 1.49 GiB | 14.86 GiB | 0.02 GiB | 23±12.9% |
| GLM-4.7-Flash-REAP-23B-A3B-absolute-heresyMoE | I1-Q4_0 | 23.0B | 12.18 GiB | 1.86 GiB | 14.85 GiB | 0.03 GiB | 51±37% |
| Pantheon-Reasoning-27B | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Qwen3.6-27B-uncensored-heretic-v2-Native-MTP-Preserved | I1-IQ3_S | 27.4B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-MTP | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Qwen3.6-27B-Fable-5-Experimental | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Qwable-5-27B-Coder | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| EVE-27b-XENO-HAT-DeepSeek-V4-Flash | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| EVE-27B-XENO-HAT | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Godoter-27B | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Reasoning-Medical-27B | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Qwopus3.6-27B-v2-abliterated | I1-IQ3_S | 27.4B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Qwen3.6-27B-Uncensored-HauhauCS-Aggressive-BF16 | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Reasoning-Medical0.1-27B | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Huihui-ThinkingCap-Qwen3.6-27B-abliterated | I1-IQ3_S | 27.4B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Semancer-27B | I1-IQ3_S | 27.8B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Darwin-28B-Coder | I1-IQ3_S | 26.9B | 11.74 GiB | 2.25 GiB | 14.85 GiB | 0.03 GiB | 23±12.9% |
| Qwen3-VL-8B-Instruct-Heretic | I1-Q4_K_S | 8.8B | 8.94 GiB | 5.06 GiB | 14.84 GiB | 0.04 GiB | 23±12.9% |
| Huihui-gemma-4-31B-it-abliterated-v2 | UD-IQ2_XXS | 32.7B | 8.00 GiB | 5.95 GiB | 14.84 GiB | 0.04 GiB | 23±12.9% |
| Rocinante-XL-16B-v1 | I1-IQ3_XS | 16.1B | 6.39 GiB | 7.59 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Qwen3.5-27B-Engineer-Deckard-Gemini | I1-IQ3_M | 27.7B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Qwen3.5-27B-HERETIC-Polaris-Advanced-Thinking-Alpha-uncensored | I1-IQ3_M | 27.4B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Qwen3.5-27B-Deckard-PKD-Heretic-Uncensored-Thinking | I1-IQ3_M | 27.4B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Qwen3.6-27B-Heretic2-Thinking | I1-IQ3_M | 27.4B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Qwen3.6-27B-Uncensored-Aggressive | I1-IQ3_M | 27.4B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Qwen-3.5-Opus-GLM-27B | I1-IQ3_M | 26.9B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Qwen3.6-27B-abliterated | I1-IQ3_M | 27.4B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| KoQweopus-3.5-27B-experimental | I1-IQ3_M | 27.8B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Webcoda-AI-27B | I1-IQ3_M | 27.4B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Qwen3.5-27B-imabari-v2 | I1-IQ3_M | 27.8B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
| Huihui-Qwen3.5-27B-abliterated | I1-IQ3_M | 27.8B | 11.72 GiB | 2.25 GiB | 14.83 GiB | 0.05 GiB | 23±12.9% |
Speed is modeled, not measured: decode is memory-bandwidth bound, so tokens per second is bytes read per token against achievable bandwidth. Mixture-of-experts models carry a wider band because only the routed experts are read each step, and few have been measured publicly.
Measured on this card
| Workload◍ | Median | Middle 50% | Runs |
|---|---|---|---|
| Image generation | 6.19 it/s | 2.48–9.21 | 72 |
| Prompt processing | 3713.61 tok/s | 3477.51–3894.03 | 22 |
| Text generation | 93.90 tok/s | 91.73–95.77 | 15 |
Aggregated from community-submitted runs, so the spread is wide by nature — it covers different models, resolutions, step counts and settings, not one controlled configuration. Read the middle 50% rather than the median alone. These figures are reproduced with attribution from vladmandic-sd-data-benchmark, which publishes no licence — so we display and link rather than redistribute them.
Questions people ask
- What AI models can a GeForce RTX 5060 Ti run?
- 1673 of 2118 indexed open-weight models fit a GeForce RTX 5060 Ti at 131,072 context with q4_0 KV cache, the largest being gemma-3-12b-it-ultra-uncensored-heretic at Q8_0. That covers text, vision-language, image, video and speech models.
- How much usable memory does a GeForce RTX 5060 Ti actually have?
- Its nameplate is 16 GB, but about 14.88 GiB is available to a model once driver and compositor overhead is accounted for.
- Is a GeForce RTX 5060 Ti fast for local AI?
- Its memory bandwidth is 448 GB/s, and that figure — not teraflops — is what governs token generation speed. Capacity decides what you can run; bandwidth decides how fast it runs.