What can Intel Arc A770 16GB run locally?

103 models fit comfortably on Intel Arc A770 16GB with 32 GB system RAM. 51 more run with tradeoffs. Top pick: Qwen 3 0.6B.

What's the recommended runner for this hardware?

llama.cpp (Vulkan). This is the runner that gives best tokens-per-second on Intel Arc A770 16GB based on windows support and the GPU backend.

What can Intel Arc A770 16GB run for chat?

Build: Intel Arc A770 16GB + — + 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
103 models

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

#1Qwen 3 0.6B

0.6B

qwen

Commercial OK

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

497

tok/s

Estimated

Weights

0.30 GB

KV cache

0.30 GB

Activations

0.02 GB

Runtime

1.00 GB

Model details →

#2Qwen 3 1.7B

1.7B

qwen

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 2.8 GBHeadroom: 13.2 GB

175

tok/s

Estimated

Weights

0.90 GB

KV cache

0.85 GB

Activations

0.05 GB

Runtime

1.00 GB

Model details →

#3TinyLlama 1.1B Chat v1.0

1.1B

llama

Commercial OK

Quant: Q4_K_MContext: 2,048VRAM: 1.8 GBHeadroom: 14.2 GB

271

tok/s

Estimated

Weights

0.60 GB

KV cache

0.14 GB

Activations

0.03 GB

Runtime

1.00 GB

Model details →

#4Gemma 2 2B Instruct

gemma

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 3.2 GBHeadroom: 12.8 GB

149

tok/s

Estimated

Weights

1.10 GB

KV cache

1.00 GB

Activations

0.06 GB

Runtime

1.00 GB

Model details →

#5DeepSeek V2 Lite Chat

15.7B

deepseek

Commercial OK

Quant: Q4_K_MContext: 2,048VRAM: 12.0 GBHeadroom: 4.0 GB

124

tok/s

Estimated

Weights

8.60 GB

KV cache

1.96 GB

Activations

0.43 GB

Runtime

1.00 GB

Model details →

#6Kumru 2B

2.4B

mistral

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 3.8 GBHeadroom: 12.2 GB

ollama run alibayram/kumru:latest

124

tok/s

Estimated

Weights

1.50 GB

KV cache

1.20 GB

Activations

0.08 GB

Runtime

1.00 GB

Model details →

#7Granite 3.0 2B Instruct

granite

Commercial OK

Quant: Q4_K_MContext: 4,096VRAM: 3.1 GBHeadroom: 12.9 GB

149

tok/s

Estimated

Weights

1.50 GB

KV cache

0.50 GB

Activations

0.08 GB

Runtime

1.00 GB

Model details →

#8Falcon 3 3B Instruct

falcon

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 4.3 GBHeadroom: 11.7 GB

tok/s

Estimated

Weights

1.70 GB

KV cache

1.50 GB

Activations

0.09 GB

Runtime

1.00 GB

Model details →

#9Dolphin 3.0 Llama 3.2 3B

dolphin

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 4.4 GBHeadroom: 11.6 GB

tok/s

Estimated

Weights

1.80 GB

KV cache

1.50 GB

Activations

0.10 GB

Runtime

1.00 GB

Model details →

#10Hermes 3 Llama 3.2 3B

hermes

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 4.4 GBHeadroom: 11.6 GB

tok/s

Estimated

Weights

1.80 GB

KV cache

1.50 GB

Activations

0.10 GB

Runtime

1.00 GB

Model details →

#11Llama 3.2 3B Instruct

llama

Commercial OK

Quant: Q8_0Context: 8,192VRAM: 6.1 GBHeadroom: 9.9 GB

ollama run llama3.2:3b

tok/s

Estimated

Weights

3.40 GB

KV cache

1.50 GB

Activations

0.18 GB

Runtime

1.00 GB

Model details →

#12Mistral Turkish v2 (brooqs)

7.2B

mistral

Quant: Q4_0Context: 8,192VRAM: 8.9 GBHeadroom: 7.1 GB

ollama run brooqs/mistral-turkish-v2:latest

tok/s

Estimated

Weights

4.10 GB

KV cache

3.60 GB

Activations

0.21 GB

Runtime

1.00 GB

Model details →

Runs with tradeoffs
51 models

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

Mistral Nemo 12B Instruct

12B

mistral

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 14.9 GBHeadroom: 1.1 GB

• Tight VRAM fit — only 1.1 GB headroom left for context growth

ollama run mistral-nemo:12b

tok/s

Estimated

Weights

7.50 GB

KV cache

6.00 GB

Activations

0.38 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 →

DeepSeek V3 Lite (16B MoE)

16B

deepseek

Commercial OK

Quant: Q4_K_MContext: 2,048VRAM: 13.0 GBHeadroom: 3.0 GB

• Tight VRAM fit — only 3.0 GB headroom left for context growth

124

tok/s

Estimated

Weights

9.50 GB

KV cache

2.00 GB

Activations

0.48 GB

Runtime

1.00 GB

Model details →

DeepSeek MoE 16B Base

16B

deepseek

Commercial OK

Quant: Q4_K_MContext: 4,096VRAM: 15.0 GBHeadroom: 1.0 GB

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

124

tok/s

Estimated

Weights

9.50 GB

KV cache

4.00 GB

Activations

0.48 GB

Runtime

1.00 GB

Model details →

Mistral Small 3 24B

24B

mistral

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 27.7 GBHeadroom: 7.5 GB

• Partial CPU offload: ~42% of layers run on CPU

ollama run mistral-small:24b

tok/s

Estimated

Weights

14.00 GB

KV cache

12.00 GB

Activations

0.71 GB

Runtime

1.00 GB

Model details →

Mistral Small 3.2 24B

24B

mistral

Commercial OK

Quant: Q4_K_MContext: 8,192VRAM: 27.7 GBHeadroom: 7.5 GB

• Partial CPU offload: ~42% of layers run on CPU

tok/s

Estimated

Weights

14.00 GB

KV cache

12.00 GB

Activations

0.71 GB

Runtime

1.00 GB

Model details →

Mistral Medium 3 24B (dense)

24B

mistral

Quant: Q4_K_MContext: 8,192VRAM: 27.7 GBHeadroom: 7.5 GB

• Partial CPU offload: ~42% of layers run on CPU

tok/s

Estimated

Weights

14.00 GB

KV cache

12.00 GB

Activations

0.71 GB

Runtime

1.00 GB

Model details →

Granite 3 MoE (3B active)

16B

granite

Commercial OK

Quant: Q4_K_MContext: 2,048VRAM: 13.0 GBHeadroom: 3.0 GB

• Tight VRAM fit — only 3.0 GB headroom left for context growth

tok/s

Estimated

Weights

9.50 GB

KV cache

2.00 GB

Activations

0.48 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

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, 69 new tradeoff

• Gemma 3 270M
• SmolLM2 135M Instruct
• SmolLM2 360M Instruct
• VBART Large (Turkish Summarization)

Shop this upgrade↗

Add a second Intel Arc A770 16GB

Launch MSRP $349 (2022). 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: 50 new comfortable

• Qwen 3 30B-A3B
• Qwen 2.5 Coder 32B Instruct
• Qwen 3 32B
• Gemma 4 31B Dense

Shop this upgrade↗

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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