What can NVIDIA GeForce RTX 4060 Ti 16GB run for long context?
Build: RTX 4060 Ti 16GB + Ryzen 5 7600 + 32GB DDR5
Runs comfortably101 models
Ranked by fit for long context use case + predicted speed. Click a row for VRAM breakdown.
Quant: Q4_K_MContext: 8,192VRAM: 5.3 GBHeadroom: 10.7 GB103tok/sEstimated
Quant: Q8_0Context: 8,192VRAM: 8.0 GBHeadroom: 8.0 GBollama run phi3.5:3.8b46tok/sEstimated
ollama run phi3.5:3.8bQuant: Q4_K_MContext: 8,192VRAM: 9.7 GBHeadroom: 6.3 GB44tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 9.7 GBHeadroom: 6.3 GB44tok/sEstimated
Quant: Q8_0Context: 8,192VRAM: 8.4 GBHeadroom: 7.6 GBollama run gemma4:e4b44tok/sEstimated
ollama run gemma4:e4bQuant: Q4_K_MContext: 8,192VRAM: 10.8 GBHeadroom: 5.2 GBollama run qwen3:8b39tok/sEstimated
ollama run qwen3:8bQuant: Q4_K_MContext: 8,192VRAM: 10.4 GBHeadroom: 5.6 GB39tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 11.1 GBHeadroom: 4.9 GB39tok/sEstimated
Quant: Q8_0Context: 8,192VRAM: 10.8 GBHeadroom: 5.2 GBollama run qwen2.5:7b25tok/sEstimated
ollama run qwen2.5:7bQuant: Q8_0Context: 8,192VRAM: 11.8 GBHeadroom: 4.2 GBollama run llama3.1:8b22tok/sEstimated
ollama run llama3.1:8bQuant: Q4_K_MContext: 8,192VRAM: 9.9 GBHeadroom: 6.1 GB44tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 9.4 GBHeadroom: 6.6 GB44tok/sEstimated
Runs with tradeoffs94 models
Tight VRAM, partial CPU offload, or context-limited.
Quant: Q4_K_MContext: 2,048VRAM: 12.8 GBHeadroom: 3.2 GB- • Tight VRAM fit — only 3.2 GB headroom left for context growth
129tok/sEstimated
- • Tight VRAM fit — only 3.2 GB headroom left for context growth
Quant: Q4_K_MContext: 8,192VRAM: 15.7 GBHeadroom: 0.3 GB- • Tight VRAM fit — only 0.3 GB headroom left for context growth
ollama run mistral-nemo:12b26tok/sEstimated
- • Tight VRAM fit — only 0.3 GB headroom left for context growth
ollama run mistral-nemo:12bQuant: Q4_K_MContext: 2,048VRAM: 12.4 GBHeadroom: 3.6 GB- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run qwen3:14b22tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run qwen3:14bQuant: Q4_K_MContext: 2,048VRAM: 12.9 GBHeadroom: 3.1 GB- • Tight VRAM fit — only 3.1 GB headroom left for context growth
ollama run qwen2.5:14b22tok/sEstimated
- • Tight VRAM fit — only 3.1 GB headroom left for context growth
ollama run qwen2.5:14bQuant: Q4_K_MContext: 2,048VRAM: 13.8 GBHeadroom: 2.2 GB- • Tight VRAM fit — only 2.2 GB headroom left for context growth
129tok/sEstimated
- • Tight VRAM fit — only 2.2 GB headroom left for context growth
Quant: Q4_K_MContext: 2,048VRAM: 13.8 GBHeadroom: 2.2 GB- • Tight VRAM fit — only 2.2 GB headroom left for context growth
103tok/sEstimated
- • Tight VRAM fit — only 2.2 GB headroom left for context growth
Quant: Q4_K_MContext: 2,048VRAM: 12.4 GBHeadroom: 3.6 GB- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run phi4:14b22tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run phi4:14bQuant: Q4_K_MContext: 2,048VRAM: 24.5 GBHeadroom: 10.7 GB- • Partial CPU offload: ~35% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run nemotron3:nano2tok/sEstimated
- • Partial CPU offload: ~35% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run nemotron3:nanoWhat if you upgraded?
Hypothetical scenarios. We re-ran the compatibility engine for each.
+32 GB system RAM
~$80–150
Doubles your CPU-offload working set. Helps when models don't quite fit in VRAM.
Unlocks: 41 new comfortable, 112 new tradeoff
- • Qwen 3 0.6B
- • Qwen 3 1.7B
- • Gemma 3 270M
- • SmolLM2 135M Instruct
Upgrade to NVIDIA RTX 2080 Ti 22GB (China-mod)
~$350
22 GB VRAM (vs your 16 GB) plus a bandwidth jump from ~288 GB/s to ~616 GB/s.
Unlocks: 68 new comfortable
- • Qwen 3 0.6B
- • Gemma 4 12B
- • Qwen3.5 9B
- • Qwen 3 1.7B
Add a second NVIDIA GeForce RTX 4060 Ti 16GB
~$449
Tensor parallelism splits the model across both cards, effectively doubling VRAM. Bandwidth doesn't double — runs ~1.5× the single-card speed in practice.
Unlocks: 115 new comfortable
- • Qwen 3 0.6B
- • Qwen 3 30B-A3B
- • Qwen 2.5 Coder 32B Instruct
- • Qwen3.6 27B
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Won't runtop 5 popular models
Need more memory than you have. Shown for orientation.
Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
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Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.
How to read these numbers
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