What can Lenovo Legion 5 Pro Gen 7 (RTX 3080 16GB) run for reasoning?
Build: Lenovo Legion 5 Pro Gen 7 (RTX 3080 16GB)
Runs comfortably78 models
Ranked by fit for reasoning use case + predicted speed. Click a row for VRAM breakdown.
Quant: Q4_K_MContext: 8,192VRAM: 10.2 GBHeadroom: 5.8 GBollama run deepseek-r1:7b108tok/sEstimated
ollama run deepseek-r1:7bQuant: Q4_K_MContext: 8,192VRAM: 11.0 GBHeadroom: 5.0 GB94tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 11.0 GBHeadroom: 5.0 GBollama run RefinedNeuro/RN_TR_R1:latest94tok/sEstimated
ollama run RefinedNeuro/RN_TR_R1:latestQuant: Q4_K_MContext: 8,192VRAM: 10.7 GBHeadroom: 5.3 GB94tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 11.6 GBHeadroom: 4.4 GB84tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 9.9 GBHeadroom: 6.1 GB108tok/sEstimated
Quant: Q4_K_MContext: 4,096VRAM: 8.2 GBHeadroom: 7.8 GB108tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 9.9 GBHeadroom: 6.1 GB108tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 10.2 GBHeadroom: 5.8 GB97tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 11.0 GBHeadroom: 5.0 GBollama run RefinedNeuro/RN_TR_R2:latest94tok/sEstimated
ollama run RefinedNeuro/RN_TR_R2:latestQuant: Q4_K_MContext: 8,192VRAM: 11.9 GBHeadroom: 4.1 GB84tok/sEstimated
Quant: Q4_0Context: 8,192VRAM: 9.7 GBHeadroom: 6.3 GBollama run brooqs/mistral-turkish-v2:latest112tok/sEstimated
ollama run brooqs/mistral-turkish-v2:latestRuns with tradeoffs94 models
Tight VRAM, partial CPU offload, or context-limited.
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-reasoning:14b54tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run phi4-reasoning:14bQuant: 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 deepseek-r1:14b54tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run deepseek-r1:14bQuant: Q4_K_MContext: 2,048VRAM: 13.8 GBHeadroom: 2.2 GB- • Tight VRAM fit — only 2.2 GB headroom left for context growth
314tok/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 phi4:14b54tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run phi4:14bQuant: Q4_K_MContext: 2,048VRAM: 12.8 GBHeadroom: 3.2 GB- • Tight VRAM fit — only 3.2 GB headroom left for context growth
314tok/sEstimated
- • Tight VRAM fit — only 3.2 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
251tok/sEstimated
- • Tight VRAM fit — only 2.2 GB headroom left for context growth
Quant: Q4_K_MContext: 4,096VRAM: 15.8 GBHeadroom: 0.2 GB- • Tight VRAM fit — only 0.2 GB headroom left for context growth
314tok/sEstimated
- • Tight VRAM fit — only 0.2 GB headroom left for context growth
Quant: Q4_K_MContext: 2,048VRAM: 23.6 GBHeadroom: 11.6 GB- • Partial CPU offload: ~32% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
2tok/sEstimated
- • Partial CPU offload: ~32% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
What 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: 64 new comfortable, 112 new tradeoff
- • Qwen 3 0.6B
- • Llama 3.2 3B Instruct
- • Qwen 3 1.7B
- • Gemma 3 270M
Upgrade to NVIDIA RTX 2080 Ti 22GB (China-mod)
~$350
22 GB VRAM (vs your 16 GB) plus a bandwidth jump from ~? GB/s to ~616 GB/s.
Unlocks: 91 new comfortable
- • Qwen 3 0.6B
- • Gemma 4 12B
- • Qwen3.5 9B
- • Llama 3.2 3B Instruct
Add a second Lenovo Legion 5 Pro Gen 7 (RTX 3080 16GB)
~$1499
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: 138 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.
—
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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