What can Lenovo Legion 5 Pro Gen 7 (RTX 3080 16GB) run for agents?
Build: Lenovo Legion 5 Pro Gen 7 (RTX 3080 16GB)
Runs comfortably42 models
Ranked by fit for agents use case + predicted speed. Click a row for VRAM breakdown.
Quant: Q4_K_MContext: 8,192VRAM: 11.0 GBHeadroom: 5.0 GBollama run hermes3:8b94tok/sEstimated
ollama run hermes3:8bQuant: Q8_0Context: 8,192VRAM: 10.8 GBHeadroom: 5.2 GBollama run qwen2.5:7b61tok/sEstimated
ollama run qwen2.5:7bQuant: Q5_K_MContext: 8,192VRAM: 10.7 GBHeadroom: 5.3 GBollama run mistral:7b95tok/sEstimated
ollama run mistral:7bQuant: Q4_K_MContext: 8,192VRAM: 11.0 GBHeadroom: 5.0 GB94tok/sEstimated
Quant: Q8_0Context: 8,192VRAM: 11.8 GBHeadroom: 4.2 GBollama run llama3.1:8b54tok/sEstimated
ollama run llama3.1:8bQuant: 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: 10.1 GBHeadroom: 5.9 GB108tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 9.9 GBHeadroom: 6.1 GB108tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 10.8 GBHeadroom: 5.2 GBollama run qwen3:8b94tok/sEstimated
ollama run qwen3:8bQuant: Q4_0Context: 8,192VRAM: 9.7 GBHeadroom: 6.3 GBollama run brooqs/mistral-turkish-v2:latest112tok/sEstimated
ollama run brooqs/mistral-turkish-v2:latestQuant: Q4_K_MContext: 8,192VRAM: 10.2 GBHeadroom: 5.8 GBollama run deepseek-r1:7b108tok/sEstimated
ollama run deepseek-r1:7bRuns with tradeoffs46 models
Tight VRAM, partial CPU offload, or context-limited.
Quant: 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 qwen2.5:14b54tok/sEstimated
- • Tight VRAM fit — only 3.1 GB headroom left for context growth
ollama run qwen2.5:14bQuant: 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 qwen3:14b54tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run qwen3:14bQuant: Q4_K_MContext: 2,048VRAM: 12.4 GBHeadroom: 3.6 GB- • Tight VRAM fit — only 3.6 GB headroom left for context growth
54tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
Quant: 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 qwen3:30b2tok/sEstimated
- • Partial CPU offload: ~35% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run qwen3:30bQuant: Q4_K_MContext: 8,192VRAM: 28.5 GBHeadroom: 6.7 GB- • Partial CPU offload: ~44% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run dolphin-mistral:24b2tok/sEstimated
- • Partial CPU offload: ~44% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run dolphin-mistral:24bQuant: Q4_K_MContext: 8,192VRAM: 23.9 GBHeadroom: 11.3 GB- • Partial CPU offload: ~33% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run qwen2.5-coder:32b2tok/sEstimated
- • Partial CPU offload: ~33% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run qwen2.5-coder:32bQuant: Q4_K_MContext: 2,048VRAM: 25.8 GBHeadroom: 9.4 GB- • Partial CPU offload: ~38% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run qwen3:32b2tok/sEstimated
- • Partial CPU offload: ~38% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run qwen3:32bQuant: Q4_K_MContext: 2,048VRAM: 25.8 GBHeadroom: 9.4 GB- • Partial CPU offload: ~38% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run qwen2.5:32b2tok/sEstimated
- • Partial CPU offload: ~38% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run qwen2.5:32bWhat if you upgraded?
Hypothetical scenarios. We re-ran the compatibility engine for each.
+32 GB system RAM
Check the current price
Adds 32 GB to your CPU-offload working set. Helps when models don't quite fit in VRAM.
Unlocks: 46 new comfortable, 57 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)
Check the current price
22 GB VRAM (vs your 16 GB) plus a bandwidth jump from ~? GB/s to ~616 GB/s.
Unlocks: 65 new comfortable
- • Qwen 3 0.6B
- • Qwen 3 14B
- • Llama 3.2 3B Instruct
- • Qwen 3 1.7B
Add a second Lenovo Legion 5 Pro Gen 7 (RTX 3080 16GB)
Launch MSRP $2,299 (2022). Now sells well below its launch price on the used market. Check the current price.
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: 86 new comfortable
- • Qwen 3 0.6B
- • Qwen 3 30B-A3B
- • Qwen 2.5 Coder 32B Instruct
- • 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.
Not enough VRAM for these models? Rent a GPU by the hour
The models above need more memory than 16 GB VRAM + 32 GB system RAM. You can rent a GPU with enough VRAM by the hour to run one of them, or to test it before you buy hardware. For daily use, owning a card usually costs less over time.
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The two tiers run on different hosts and terms. Check which tier a pod is on before a long job.
Rent on RunPodVast.ai
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How to read these numbers
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