What can AMD Radeon RX 7900 XTX run for long context?
Build: RX 7900 XTX + Ryzen 9 7950X + 64GB DDR5 (Linux/ROCm)
Runs comfortably142 models
Ranked by fit for long context use case + predicted speed. Click a row for VRAM breakdown.
Quant: Q8_0Context: 8,192VRAM: 8.6 GBHeadroom: 15.4 GBTTFT: instantollama run gemma4:e4b124tok/sEstimated
ollama run gemma4:e4bQuant: Q8_0Context: 8,192VRAM: 8.2 GBHeadroom: 15.8 GBTTFT: instantollama run phi3.5:3.8b131tok/sEstimated
ollama run phi3.5:3.8bQuant: Q4_K_MContext: 8,192VRAM: 9.9 GBHeadroom: 14.1 GBTTFT: fast125tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 9.9 GBHeadroom: 14.1 GBTTFT: fast125tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 5.5 GBHeadroom: 18.5 GBTTFT: instant292tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 10.6 GBHeadroom: 13.4 GBTTFT: fast109tok/sEstimated
Quant: Q4_K_MContext: 8,192VRAM: 11.3 GBHeadroom: 12.7 GBTTFT: fast109tok/sEstimated
Quant: Q8_0Context: 8,192VRAM: 11.0 GBHeadroom: 13.0 GBTTFT: fastollama run qwen2.5:7b71tok/sEstimated
ollama run qwen2.5:7bQuant: Q5_K_MContext: 8,192VRAM: 17.1 GBHeadroom: 6.9 GBTTFT: fastollama run mistral-nemo:12b64tok/sEstimated
ollama run mistral-nemo:12bQuant: Q4_K_MContext: 8,192VRAM: 17.8 GBHeadroom: 6.2 GBTTFT: fastollama run qwen3:14b62tok/sEstimated
ollama run qwen3:14bQuant: Q8_0Context: 8,192VRAM: 14.6 GBHeadroom: 9.4 GBTTFT: fastollama run qwen3:8b62tok/sEstimated
ollama run qwen3:8bQuant: Q4_K_MContext: 8,192VRAM: 10.1 GBHeadroom: 13.9 GBTTFT: fast125tok/sEstimated
Runs with tradeoffs74 models
Tight VRAM, partial CPU offload, or context-limited.
Quant: Q5_K_MContext: 8,192VRAM: 20.0 GBHeadroom: 4.0 GBTTFT: fast- • Tight VRAM fit — only 4.0 GB headroom left for context growth
ollama run qwen2.5:14b55tok/sEstimated
- • Tight VRAM fit — only 4.0 GB headroom left for context growth
ollama run qwen2.5:14bQuant: Q4_K_MContext: 2,048VRAM: 20.3 GBHeadroom: 3.7 GBTTFT: noticeable- • Tight VRAM fit — only 3.7 GB headroom left for context growth
34tok/sEstimated
- • Tight VRAM fit — only 3.7 GB headroom left for context growth
Quant: Q4_K_MContext: 2,048VRAM: 22.2 GBHeadroom: 1.8 GBTTFT: noticeable- • Tight VRAM fit — only 1.8 GB headroom left for context growth
ollama run gemma3:27b32tok/sEstimated
- • Tight VRAM fit — only 1.8 GB headroom left for context growth
ollama run gemma3:27bQuant: Q4_K_MContext: 8,192VRAM: 20.6 GBHeadroom: 3.4 GBTTFT: noticeable- • Tight VRAM fit — only 3.4 GB headroom left for context growth
ollama run muse-glimmer29tok/sEstimated
- • Tight VRAM fit — only 3.4 GB headroom left for context growth
ollama run muse-glimmerQuant: Q4_K_MContext: 8,192VRAM: 59.5 GBHeadroom: 2.9 GBTTFT: fast- • Partial CPU offload: ~60% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
8tok/sEstimated
- • Partial CPU offload: ~60% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
Quant: Q8_0Context: 8,192VRAM: 50.6 GBHeadroom: 11.8 GBTTFT: noticeable- • Partial CPU offload: ~53% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run nemotron3:nano2tok/sEstimated
- • Partial CPU offload: ~53% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run nemotron3:nanoQuant: Q4_K_MContext: 8,192VRAM: 41.6 GBHeadroom: 20.8 GBTTFT: noticeable- • Partial CPU offload: ~42% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run command-r:35b4tok/sEstimated
- • Partial CPU offload: ~42% of layers run on CPU
- • CPU is the bottleneck — upgrading RAM bandwidth helps more than VRAM here
ollama run command-r:35bQuant: Q8_0Context: 8,192VRAM: 20.6 GBHeadroom: 3.4 GBTTFT: fast- • Tight VRAM fit — only 3.4 GB headroom left for context growth
ollama run llama3.2-vision:11b45tok/sEstimated
- • Tight VRAM fit — only 3.4 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
~$80–150
Doubles your CPU-offload working set. Helps when models don't quite fit in VRAM.
Unlocks: 41 new comfortable, 80 new tradeoff
- • Qwen 3 0.6B
- • Qwen 3 1.7B
- • Gemma 3 270M
- • SmolLM2 135M Instruct
Upgrade to AMD Instinct MI210
see current pricing
64 GB VRAM (vs your 24 GB) plus a bandwidth jump from ~960 GB/s to ~1638 GB/s.
Unlocks: 112 new comfortable
- • Qwen 3 0.6B
- • Qwen 3 30B-A3B
- • Qwen 2.5 Coder 32B Instruct
- • Qwen3.6 27B
Add a second AMD Radeon RX 7900 XTX
~$899
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: 94 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 (24 GB) + 60% of system RAM (38 GB) combined.
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Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.
—
Even with CPU offload, needs more memory than your VRAM (24 GB) + 60% of system RAM (38 GB) combined.
How to read these numbers
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