What can AMD Radeon RX 9070 XT run locally?

16 models fit comfortably on AMD Radeon RX 9070 XT with 32 GB system RAM. 16 more run with tradeoffs. Top pick: Gemma 4 E2B (Effective 2B).

What's the recommended runner for this hardware?

llama.cpp (Vulkan). This is the runner that gives best tokens-per-second on AMD Radeon RX 9070 XT based on windows support and the GPU backend.

What can AMD Radeon RX 9070 XT run for vision?

Build: AMD Radeon RX 9070 XT + — + 32 GB RAM (windows)

Memory: 16 GB VRAM + 32 GB system RAM

Runner: llama.cpp (Vulkan)

Any Chat Coding Agents Reasoning Vision Long context Creative

Runs comfortably
16 models

Ranked by fit for vision use case + predicted speed. Click a row for VRAM breakdown.

#1Gemma 4 E2B (Effective 2B)

gemma

Commercial OK

Quant: Q8_0Context: 8,192VRAM: 4.3 GBHeadroom: 11.7 GB

ollama run gemma4:e2b

136

tok/s

Estimated

Weights

2.20 GB

KV cache

1.00 GB

Activations

0.12 GB

Runtime

1.00 GB

Model details →

#2Moondream 2

1.9B

other

Commercial OK

Quant: Q4_K_MContext: 2,048VRAM: 2.5 GBHeadroom: 13.5 GB

253

tok/s

Estimated

Weights

1.20 GB

KV cache

0.24 GB

Activations

0.06 GB

Runtime

1.00 GB

Model details →

#3Qwen 2.5-VL 3B

qwen

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 4.6 GBHeadroom: 11.4 GB

160

tok/s

Estimated

Weights

2.00 GB

KV cache

1.50 GB

Activations

0.11 GB

Runtime

1.00 GB

Model details →

#4Phi-3.5 Vision

4.2B

phi

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 5.7 GBHeadroom: 10.3 GB

114

tok/s

Estimated

Weights

2.50 GB

KV cache

2.10 GB

Activations

0.13 GB

Runtime

1.00 GB

Model details →

#5LLaVA 1.6 Mistral 7B

other

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 9.2 GBHeadroom: 6.8 GB

tok/s

Estimated

Weights

4.50 GB

KV cache

3.50 GB

Activations

0.23 GB

Runtime

1.00 GB

Model details →

#6LLaVA-OneVision 7B

other

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 9.2 GBHeadroom: 6.8 GB

tok/s

Estimated

Weights

4.50 GB

KV cache

3.50 GB

Activations

0.23 GB

Runtime

1.00 GB

Model details →

#7Qwen 2-VL 7B

qwen

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 9.3 GBHeadroom: 6.7 GB

tok/s

Estimated

Weights

4.60 GB

KV cache

3.50 GB

Activations

0.24 GB

Runtime

1.00 GB

Model details →

#8Qwen 2.5-VL 7B

qwen

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 9.1 GBHeadroom: 6.9 GB

tok/s

Estimated

Weights

4.40 GB

KV cache

3.50 GB

Activations

0.23 GB

Runtime

1.00 GB

Model details →

#9Gemma 4 E4B (Effective 4B)

gemma

Commercial OK

Quant: Q8_0Context: 8,192VRAM: 7.6 GBHeadroom: 8.4 GB

ollama run gemma4:e4b

tok/s

Estimated

Weights

4.40 GB

KV cache

2.00 GB

Activations

0.23 GB

Runtime

1.00 GB

Model details →

#10Gemma 3 4B

gemma

Commercial OK

Quant: Q8_0Context: 8,192VRAM: 7.6 GBHeadroom: 8.4 GB

ollama run gemma3:4b

tok/s

Estimated

Weights

4.40 GB

KV cache

2.00 GB

Activations

0.23 GB

Runtime

1.00 GB

Model details →

#11MiniCPM-V 3 8B

minicpm

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 10.3 GBHeadroom: 5.7 GB

tok/s

Estimated

Weights

5.00 GB

KV cache

4.00 GB

Activations

0.26 GB

Runtime

1.00 GB

Model details →

#12MiniCPM-V 2.6 8B

minicpm

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 10.3 GBHeadroom: 5.7 GB

tok/s

Estimated

Weights

5.00 GB

KV cache

4.00 GB

Activations

0.26 GB

Runtime

1.00 GB

Model details →

Runs with tradeoffs
16 models

Tight VRAM, partial CPU offload, or context-limited.

Qwen3.5 9B

qwen

Commercial OK

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 qwen3.5:9b

tok/s

Estimated

Weights

6.60 GB

KV cache

4.50 GB

Activations

0.34 GB

Runtime

1.00 GB

Model details →

Llama 3.2 11B Vision Instruct

11B

llama

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 14.8 GBHeadroom: 1.2 GB

• Tight VRAM fit — only 1.2 GB headroom left for context growth

ollama run llama3.2-vision:11b

tok/s

Estimated

Weights

7.90 GB

KV cache

5.50 GB

Activations

0.40 GB

Runtime

1.00 GB

Model details →

Llama 3.2 11B Vision

11B

llama

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 13.3 GBHeadroom: 2.7 GB

• Tight VRAM fit — only 2.7 GB headroom left for context growth

tok/s

Estimated

Weights

6.50 GB

KV cache

5.50 GB

Activations

0.33 GB

Runtime

1.00 GB

Model details →

Gemma 4 12B

12B

gemma

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 15.0 GBHeadroom: 1.0 GB

• Tight VRAM fit — only 1.0 GB headroom left for context growth

ollama run gemma4:12b

tok/s

Estimated

Weights

7.60 GB

KV cache

6.00 GB

Activations

0.39 GB

Runtime

1.00 GB

Model details →

Gemma 3 12B

12B

gemma

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 14.7 GBHeadroom: 1.3 GB

• Tight VRAM fit — only 1.3 GB headroom left for context growth

ollama run gemma3:12b

tok/s

Estimated

Weights

7.30 GB

KV cache

6.00 GB

Activations

0.37 GB

Runtime

1.00 GB

Model details →

Pixtral 12B

12B

mistral

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 14.4 GBHeadroom: 1.6 GB

• Tight VRAM fit — only 1.6 GB headroom left for context growth

ollama run pixtral:12b

tok/s

Estimated

Weights

7.00 GB

KV cache

6.00 GB

Activations

0.36 GB

Runtime

1.00 GB

Model details →

Ministral 3 14B

14B

mistral

Commercial OK

Quant: Q4_K_MContext: 2,048VRAM: 12.3 GBHeadroom: 3.7 GB

• Tight VRAM fit — only 3.7 GB headroom left for context growth

ollama run ministral-3:14b

tok/s

Estimated

Weights

9.10 GB

KV cache

1.75 GB

Activations

0.46 GB

Runtime

1.00 GB

Model details →

Phi-4 Multimodal

14B

phi

Commercial OK

Quant: Q4_K_MContext: 2,048VRAM: 12.2 GBHeadroom: 3.8 GB

• Tight VRAM fit — only 3.8 GB headroom left for context growth

tok/s

Estimated

Weights

9.00 GB

KV cache

1.75 GB

Activations

0.45 GB

Runtime

1.00 GB

Model details →

What 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: 138 new comfortable, 102 new tradeoff

• Qwen 3 0.6B
• Llama 3.1 8B Instruct
• Qwen 3 8B
• Llama 3.2 3B Instruct

Shop this upgrade↗

Upgrade to AMD Radeon RX 7900 XT

~$729

20 GB VRAM (vs your 16 GB) plus a bandwidth jump from ~644 GB/s to ~800 GB/s.

Unlocks: 147 new comfortable

• Qwen 3 0.6B
• Llama 3.1 8B Instruct
• Qwen 3 8B
• Gemma 4 12B

Shop this upgrade↗

Add a second AMD Radeon RX 9070 XT

~$649

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: 209 new comfortable

• Qwen 3 0.6B
• Llama 3.1 8B Instruct
• Qwen 3 30B-A3B
• Qwen 2.5 Coder 32B Instruct

Shop this upgrade↗

Some links above are affiliate links. We may earn a commission at no extra cost to you. How we make money.

Won't run
top 5 popular models

Need more memory than you have. Shown for orientation.

DeepSeek V4 Pro (1.6T MoE)

1600B

deepseek

Commercial OK