What can NVIDIA GeForce RTX 5090 run for vision?
Build: NVIDIA GeForce RTX 5090 + — + 32 GB RAM (windows)
Runs comfortably24 models
Ranked by fit for vision use case + predicted speed. Click a row for VRAM breakdown.
Quant: Q8_0Context: 8,192VRAM: 8.4 GBHeadroom: 23.6 GBTTFT: instantollama run gemma4:e4b274tok/sEstimated
ollama run gemma4:e4bQuant: Q8_0Context: 8,192VRAM: 8.4 GBHeadroom: 23.6 GBTTFT: instantollama run gemma3:4b274tok/sEstimated
ollama run gemma3:4bQuant: Q8_0Context: 8,192VRAM: 5.1 GBHeadroom: 26.9 GBTTFT: instantollama run gemma4:e2b548tok/sEstimated
ollama run gemma4:e2bQuant: Q4_K_MContext: 8,192VRAM: 6.5 GBHeadroom: 25.5 GBTTFT: instant459tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 11.1 GBHeadroom: 20.9 GBTTFT: fast241tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 9.9 GBHeadroom: 22.1 GBTTFT: fast276tok/sEstimated
Quant: Q4_K_MContext: 2,048VRAM: 3.3 GBHeadroom: 28.7 GBTTFT: instant1015tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 10.1 GBHeadroom: 21.9 GBTTFT: fast276tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 10.0 GBHeadroom: 22.0 GBTTFT: fast276tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 10.0 GBHeadroom: 22.0 GBTTFT: fast276tok/sEstimated
Quant: Q4_K_MContext: 4,096VRAM: 9.3 GBHeadroom: 22.7 GBTTFT: fast241tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 17.7 GBHeadroom: 14.3 GBTTFT: fast139tok/sEstimated
Runs with tradeoffs1 models
Tight VRAM, partial CPU offload, or context-limited.
Quant: Q4_K_MContext: 8,192VRAM: 31.6 GBHeadroom: 0.4 GBTTFT: noticeable- • Tight VRAM fit — only 0.4 GB headroom left for context growth
74tok/sEstimated
- • Tight VRAM fit — only 0.4 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: 104 new comfortable, 22 new tradeoff
- • Qwen 3 0.6B
- • Llama 3.1 8B Instruct
- • Qwen 3 30B-A3B
- • Qwen 2.5 Coder 32B Instruct
Upgrade to NVIDIA A100 40GB
Launch MSRP $11,000 (2020). Check the current price.
40 GB VRAM (vs your 32 GB) plus a bandwidth jump from ~1792 GB/s to ~? GB/s.
Unlocks: 101 new comfortable
- • Qwen 3 0.6B
- • Llama 3.1 8B Instruct
- • Qwen 3 30B-A3B
- • Qwen 2.5 Coder 32B Instruct
Add a second NVIDIA GeForce RTX 5090
Launch MSRP $1,999 (2025). 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: 122 new comfortable
- • Qwen 3 0.6B
- • Llama 3.1 8B Instruct
- • Qwen 3 30B-A3B
- • Llama 3.3 70B Instruct
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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 (32 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (32 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (32 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (32 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (32 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (32 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (32 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (32 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (32 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (32 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 32 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.
RunPod
billed per GPU-hourHourly GPU pods, in community-cloud and secure-cloud tiers.
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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Host quality varies. Filter for verified hosts and check the host's reliability before a long run.
Rent on Vast.aiReferral links: RunLocalAI may earn a commission or account credits if you sign up and rent, at no extra cost to you. Hourly rates and which GPUs are listed change all the time, so check the provider's page before you start. Editorial opinions are independent of the referral relationship; see how we make money.
How to read these numbers
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