What can NVIDIA GeForce RTX 4090 Mobile run for creative?
Build: NVIDIA GeForce RTX 4090 Mobile + — + 32 GB RAM (windows)
Runs comfortably84 models
Ranked by fit for creative use case + predicted speed. Click a row for VRAM breakdown.
Quant: Q4_K_MContext: 8,192VRAM: 11.0 GBHeadroom: 5.0 GBollama run hermes3:8b128tok/sEstimated
ollama run hermes3:8bQuant: Q4_K_MContext: 8,192VRAM: 5.2 GBHeadroom: 10.8 GB341tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 5.2 GBHeadroom: 10.8 GB341tok/sEstimated
Quant: Q8_0Context: 8,192VRAM: 8.4 GBHeadroom: 7.6 GBollama run gemma4:e4b145tok/sEstimated
ollama run gemma4:e4bQuant: Q4_K_MContext: 8,192VRAM: 4.0 GBHeadroom: 12.0 GB511tok/sEstimated
Quant: Q8_0Context: 8,192VRAM: 8.4 GBHeadroom: 7.6 GBollama run gemma3:4b145tok/sEstimated
ollama run gemma3:4bQuant: Q8_0Context: 8,192VRAM: 5.1 GBHeadroom: 10.9 GBollama run gemma4:e2b291tok/sEstimated
ollama run gemma4:e2bQuant: Q4_K_MContext: 8,192VRAM: 9.7 GBHeadroom: 6.3 GBollama run codegemma:7b146tok/sEstimated
ollama run codegemma:7bQuant: Q4_K_MContext: 8,192VRAM: 11.6 GBHeadroom: 4.4 GB114tok/sEstimated
Quant: BF16Context: 8,192VRAM: 9.6 GBHeadroom: 6.4 GB103tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 10.8 GBHeadroom: 5.2 GBollama run qwen3:8b128tok/sEstimated
ollama run qwen3:8bQuant: Q4_K_MContext: 8,192VRAM: 3.6 GBHeadroom: 12.4 GB602tok/sEstimated
Runs with tradeoffs62 models
Tight VRAM, partial CPU offload, or context-limited.
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 gemma2:9b114tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run gemma2:9bQuant: Q4_K_MContext: 8,192VRAM: 12.5 GBHeadroom: 3.5 GB- • Tight VRAM fit — only 3.5 GB headroom left for context growth
ollama run alibayram/turkish-gemma-9b-v0.1:latest111tok/sEstimated
- • Tight VRAM fit — only 3.5 GB headroom left for context growth
ollama run alibayram/turkish-gemma-9b-v0.1:latestQuant: Q4_K_MContext: 8,192VRAM: 28.5 GBHeadroom: 6.7 GB- • Partial CPU offload: ~44% of layers run on CPU
ollama run dolphin-mistral:24b43tok/sEstimated
- • Partial CPU offload: ~44% of layers run on CPU
ollama run dolphin-mistral:24bQuant: 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 gemma3:12b85tok/sEstimated
- • Tight VRAM fit — only 0.5 GB headroom left for context growth
ollama run gemma3:12bQuant: Q4_K_MContext: 2,048VRAM: 12.8 GBHeadroom: 3.2 GB- • Tight VRAM fit — only 3.2 GB headroom left for context growth
426tok/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
426tok/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
426tok/sEstimated
- • Tight VRAM fit — only 0.2 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
341tok/sEstimated
- • Tight VRAM fit — only 2.2 GB headroom left for context growth
What 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: 13 new comfortable, 78 new tradeoff
- • Qwen 3 0.6B
- • Gemma 3 270M
- • SmolLM2 135M Instruct
- • TinyLlama 1.1B Chat v1.0
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: 32 new comfortable
- • Qwen 3 0.6B
- • Qwen 3 14B
- • Gemma 3 270M
- • Phi-4 14B
Add a second NVIDIA GeForce RTX 4090 Mobile
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: 63 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.
How to read these numbers
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