What can NVIDIA GeForce RTX 5070 Ti run for chat?
Build: RTX 5070 Ti + Ryzen 7 9700X + 32GB DDR5
Runs comfortably133 models
Ranked by fit for chat use case + predicted speed. Click a row for VRAM breakdown.
Quant: Q4_K_MContext: 8,192VRAM: 2.4 GBHeadroom: 13.6 GB1608tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 10.8 GBHeadroom: 5.2 GBollama run qwen3:8b121tok/sEstimated
ollama run qwen3:8bQuant: Q8_0Context: 8,192VRAM: 6.9 GBHeadroom: 9.1 GBollama run llama3.2:3b183tok/sEstimated
ollama run llama3.2:3bQuant: Q4_K_MContext: 8,192VRAM: 3.6 GBHeadroom: 12.4 GB567tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 11.1 GBHeadroom: 4.9 GBollama run dolphin3:8b121tok/sEstimated
ollama run dolphin3:8bQuant: Q4_K_MContext: 2,048VRAM: 2.6 GBHeadroom: 13.4 GB877tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 4.0 GBHeadroom: 12.0 GB482tok/sEstimated
Quant: Q5_K_MContext: 8,192VRAM: 10.7 GBHeadroom: 5.3 GBollama run mistral:7b121tok/sEstimated
ollama run mistral:7bQuant: Q4_K_MContext: 4,096VRAM: 7.6 GBHeadroom: 8.4 GB138tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 4.6 GBHeadroom: 11.4 GBollama run alibayram/kumru:latest402tok/sEstimated
ollama run alibayram/kumru:latestQuant: Q4_K_MContext: 8,192VRAM: 9.4 GBHeadroom: 6.6 GB138tok/sEstimated
Quant: Q4_K_MContext: 2,048VRAM: 2.6 GBHeadroom: 13.4 GB877tok/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
402tok/sEstimated
- • Tight VRAM fit — only 3.2 GB headroom left for context growth
Quant: Q4_K_MContext: 8,192VRAM: 12.4 GBHeadroom: 3.6 GB- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run gemma2:9b107tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run gemma2:9bQuant: Q4_K_MContext: 8,192VRAM: 13.7 GBHeadroom: 2.3 GB- • Tight VRAM fit — only 2.3 GB headroom left for context growth
88tok/sEstimated
- • Tight VRAM fit — only 2.3 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:12b80tok/sEstimated
- • Tight VRAM fit — only 0.3 GB headroom left for context growth
ollama run mistral-nemo:12bQuant: Q4_K_MContext: 8,192VRAM: 15.5 GBHeadroom: 0.5 GB- • Tight VRAM fit — only 0.5 GB headroom left for context growth
ollama run gemma3:12b80tok/sEstimated
- • Tight VRAM fit — only 0.5 GB headroom left for context growth
ollama run gemma3:12bQuant: Q4_K_MContext: 4,096VRAM: 12.4 GBHeadroom: 3.6 GB- • Tight VRAM fit — only 3.6 GB headroom left for context growth
80tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
Quant: Q4_K_MContext: 4,096VRAM: 12.6 GBHeadroom: 3.4 GB- • Tight VRAM fit — only 3.4 GB headroom left for context growth
74tok/sEstimated
- • Tight VRAM fit — only 3.4 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 qwen3:14b69tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run qwen3:14bWhat 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: 9 new comfortable, 112 new tradeoff
- • Gemma 3 270M
- • SmolLM2 135M Instruct
- • SmolLM2 360M Instruct
- • VBART Large (Turkish Summarization)
Upgrade to NVIDIA RTX 2080 Ti 22GB (China-mod)
~$350
22 GB VRAM (vs your 16 GB) plus a bandwidth jump from ~896 GB/s to ~616 GB/s.
Unlocks: 36 new comfortable
- • Gemma 4 12B
- • Qwen3.5 9B
- • Qwen 3 14B
- • Gemma 3 270M
Add a second NVIDIA GeForce RTX 5070 Ti
~$849
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: 83 new comfortable
- • Qwen 3 30B-A3B
- • Qwen 2.5 Coder 32B Instruct
- • Qwen3.6 27B
- • Qwen 3 32B
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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.
—
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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