What can NVIDIA RTX A5000 run for chat?
Build: NVIDIA RTX A5000 + — + 32 GB RAM (windows)
Runs comfortably125 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: 21.6 GB2692tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 3.6 GBHeadroom: 20.4 GB950tok/sEstimated
Quant: Q8_0Context: 8,192VRAM: 6.9 GBHeadroom: 17.1 GBollama run llama3.2:3b306tok/sEstimated
ollama run llama3.2:3bQuant: Q4_K_MContext: 8,192VRAM: 15.5 GBHeadroom: 8.5 GBollama run gemma3:12b135tok/sEstimated
ollama run gemma3:12bQuant: Q4_K_MContext: 2,048VRAM: 2.6 GBHeadroom: 21.4 GB1468tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 4.0 GBHeadroom: 20.0 GB807tok/sEstimated
Quant: Q5_K_MContext: 8,192VRAM: 10.7 GBHeadroom: 13.3 GBollama run mistral:7b203tok/sEstimated
ollama run mistral:7bQuant: Q4_K_MContext: 8,192VRAM: 18.7 GBHeadroom: 5.3 GB673tok/sEstimated
Quant: Q4_K_MContext: 4,096VRAM: 7.6 GBHeadroom: 16.4 GB231tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 4.6 GBHeadroom: 19.4 GBollama run alibayram/kumru:latest673tok/sEstimated
ollama run alibayram/kumru:latestQuant: Q4_K_MContext: 8,192VRAM: 10.2 GBHeadroom: 13.8 GBollama run RefinedNeuro/Turkcell-LLM-7b-v1:latest218tok/sEstimated
ollama run RefinedNeuro/Turkcell-LLM-7b-v1:latestQuant: Q4_0Context: 8,192VRAM: 9.7 GBHeadroom: 14.3 GBollama run brooqs/mistral-turkish-v2:latest241tok/sEstimated
ollama run brooqs/mistral-turkish-v2:latestRuns with tradeoffs32 models
Tight VRAM, partial CPU offload, or context-limited.
Quant: Q4_K_MContext: 2,048VRAM: 21.9 GBHeadroom: 2.1 GB- • Tight VRAM fit — only 2.1 GB headroom left for context growth
ollama run gemma4:26b-moe62tok/sEstimated
- • Tight VRAM fit — only 2.1 GB headroom left for context growth
ollama run gemma4:26b-moeQuant: Q4_K_MContext: 2,048VRAM: 22.0 GBHeadroom: 2.0 GB- • Tight VRAM fit — only 2.0 GB headroom left for context growth
ollama run gemma3:27b60tok/sEstimated
- • Tight VRAM fit — only 2.0 GB headroom left for context growth
ollama run gemma3:27bQuant: Q4_K_MContext: 8,192VRAM: 36.2 GBHeadroom: 7.0 GB- • Partial CPU offload: ~34% of layers run on CPU
ollama run gemma4:31b52tok/sEstimated
- • Partial CPU offload: ~34% of layers run on CPU
ollama run gemma4:31bQuant: Q4_K_MContext: 8,192VRAM: 37.8 GBHeadroom: 5.4 GB- • Partial CPU offload: ~36% of layers run on CPU
50tok/sEstimated
- • Partial CPU offload: ~36% of layers run on CPU
Quant: Q4_K_MContext: 8,192VRAM: 39.8 GBHeadroom: 3.4 GB- • Partial CPU offload: ~40% of layers run on CPU
ollama run yi:34b47tok/sEstimated
- • Partial CPU offload: ~40% of layers run on CPU
ollama run yi:34bQuant: Q4_K_MContext: 2,048VRAM: 37.1 GBHeadroom: 6.1 GB- • Partial CPU offload: ~35% of layers run on CPU
ollama run mixtral:8x7b34tok/sEstimated
- • Partial CPU offload: ~35% of layers run on CPU
ollama run mixtral:8x7bQuant: Q4_K_MContext: 2,048VRAM: 39.8 GBHeadroom: 3.4 GB- • Partial CPU offload: ~40% of layers run on CPU
135tok/sEstimated
- • Partial CPU offload: ~40% of layers run on CPU
Quant: Q8_0Context: 8,192VRAM: 20.4 GBHeadroom: 3.6 GB- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run llama3.2-vision:11b83tok/sEstimated
- • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run llama3.2-vision:11bWhat 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: 5 new comfortable, 48 new tradeoff
- • Gemma 3 270M
- • SmolLM2 135M Instruct
- • SmolLM2 360M Instruct
- • VBART Large (Turkish Summarization)
Upgrade to NVIDIA GeForce RTX 5090
Launch MSRP $1,999 (2025). Check the current price.
32 GB VRAM (vs your 24 GB) plus a bandwidth jump from ~? GB/s to ~1792 GB/s.
Unlocks: 29 new comfortable
- • Qwen 3 30B-A3B
- • Qwen 2.5 Coder 32B Instruct
- • Qwen 3 32B
- • Gemma 4 31B Dense
Add a second NVIDIA RTX A5000
Launch MSRP $2,500 (2021). 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: 37 new comfortable
- • Qwen 3 30B-A3B
- • Qwen 2.5 Coder 32B Instruct
- • Qwen 3 32B
- • Gemma 4 31B Dense
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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 (24 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 GB) combined.
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (19 GB) combined.
How to read these numbers
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