RUNLOCALAIv38
→WILL IT RUNBEST GPUCOMPARETROUBLESHOOTSTARTPULSEMODELSHARDWARETOOLSBENCH
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RUNLOCALAI · v38
Will it run? / Intel Arc A770 16GB / creative

What can Intel Arc A770 16GB run for creative?

Build: Intel Arc A770 16GB + — + 32 GB RAM (windows)

Memory: 16 GB VRAM + 32 GB system RAM
Runner: llama.cpp (Vulkan)
AnyChatCodingAgentsReasoningVisionLong contextCreative

Runs comfortably
50 models

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

#1Hermes 3 Llama 3.1 8B
8B
hermes
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 9.1 GBHeadroom: 6.9 GB
ollama run hermes3:8b
52
tok/s
E
Weights
4.83 GB
KV cache
1.00 GB
Activations
2.29 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#2Gemma 2 9B Instruct
9B
gemma
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 9.9 GBHeadroom: 6.1 GB
ollama run gemma2:9b
46
tok/s
E
Weights
5.43 GB
KV cache
1.13 GB
Activations
2.32 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#3SmolLM 2 1.7B Instruct
1.7B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 11.1 GBHeadroom: 4.9 GB
245
tok/s
E
Weights
1.03 GB
KV cache
0.85 GB
Activations
8.24 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#4EXAONE 3.5 2.4B
2.4B
exaone
Quant: Q4_K_MContext: 8,192VRAM: 11.9 GBHeadroom: 4.1 GB
174
tok/s
E
Weights
1.45 GB
KV cache
1.20 GB
Activations
8.26 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#5Qwen 2.5 1.5B Instruct
1.5B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 10.9 GBHeadroom: 5.1 GB
278
tok/s
E
Weights
0.91 GB
KV cache
0.75 GB
Activations
8.24 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#6Qwen 2.5 Coder 1.5B
1.5B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 10.9 GBHeadroom: 5.1 GB
278
tok/s
E
Weights
0.91 GB
KV cache
0.75 GB
Activations
8.24 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#7RWKV 7 'Goose' 1.5B
1.5B
rwkv
Commercial OK
Quant: Q5_K_MContext: 8,192VRAM: 11.0 GBHeadroom: 5.0 GB
244
tok/s
E
Weights
1.03 GB
KV cache
0.75 GB
Activations
8.24 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#8Moondream 2
1.9B
other
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 4.5 GBHeadroom: 11.5 GB
219
tok/s
E
Weights
1.15 GB
KV cache
0.24 GB
Activations
2.11 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#9Granite 3.0 2B Instruct
2B
granite
Commercial OK
Quant: Q4_K_MContext: 4,096VRAM: 6.9 GBHeadroom: 9.1 GB
208
tok/s
E
Weights
1.21 GB
KV cache
0.50 GB
Activations
4.16 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#10DeepSeek R1 Distill Qwen 1.5B
1.5B
deepseek
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 10.9 GBHeadroom: 5.1 GB
278
tok/s
E
Weights
0.91 GB
KV cache
0.75 GB
Activations
8.24 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#11Nemotron Mini 4B Instruct
4B
other
Commercial OK
Quant: Q4_K_MContext: 4,096VRAM: 8.6 GBHeadroom: 7.4 GB
104
tok/s
E
Weights
2.42 GB
KV cache
1.00 GB
Activations
4.22 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
#12CodeGemma 7B
7B
gemma
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 8.4 GBHeadroom: 7.6 GB
ollama run codegemma:7b
60
tok/s
E
Weights
4.23 GB
KV cache
0.88 GB
Activations
2.26 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →

Runs with tradeoffs
69 models

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

Dolphin 3.0 Llama 3.2 3B
3B
dolphin
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 12.6 GBHeadroom: 3.4 GB
  • • Tight VRAM fit — only 3.4 GB headroom left for context growth
139
tok/s
E
Weights
1.81 GB
KV cache
1.50 GB
Activations
8.28 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
Hermes 3 Llama 3.2 3B
3B
hermes
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 12.6 GBHeadroom: 3.4 GB
  • • Tight VRAM fit — only 3.4 GB headroom left for context growth
139
tok/s
E
Weights
1.81 GB
KV cache
1.50 GB
Activations
8.28 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
Gemma 4 E2B (Effective 2B)
2B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 12.4 GBHeadroom: 3.6 GB
  • • Tight VRAM fit — only 3.6 GB headroom left for context growth
ollama run gemma4:e2b
118
tok/s
E
Weights
2.13 GB
KV cache
1.00 GB
Activations
8.30 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
StarCoder 2 3B
3B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 12.6 GBHeadroom: 3.4 GB
  • • Tight VRAM fit — only 3.4 GB headroom left for context growth
139
tok/s
E
Weights
1.81 GB
KV cache
1.50 GB
Activations
8.28 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
Qwen 2.5 3B Instruct
3B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 12.6 GBHeadroom: 3.4 GB
  • • Tight VRAM fit — only 3.4 GB headroom left for context growth
139
tok/s
E
Weights
1.81 GB
KV cache
1.50 GB
Activations
8.28 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
Qwen 2.5-VL 3B
3B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 12.6 GBHeadroom: 3.4 GB
  • • Tight VRAM fit — only 3.4 GB headroom left for context growth
139
tok/s
E
Weights
1.81 GB
KV cache
1.50 GB
Activations
8.28 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
Granite 3 MoE (3B active)
16B
granite
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 15.2 GBHeadroom: 0.8 GB
  • • Tight VRAM fit — only 0.8 GB headroom left for context growth
139
tok/s
E
Weights
9.66 GB
KV cache
2.00 GB
Activations
2.53 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →
DeepSeek V3 Lite (16B MoE)
16B
deepseek
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 15.2 GBHeadroom: 0.8 GB
  • • Tight VRAM fit — only 0.8 GB headroom left for context growth
174
tok/s
E
Weights
9.66 GB
KV cache
2.00 GB
Activations
2.53 GB
Runtime
1.00 GB
Model details →Run-on benchmark page →

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: 7 new comfortable, 78 new tradeoff

  • • Gemma 3 1B
  • • Llama 3.2 1B Instruct
  • • Whisper Large v3 Turbo
  • • SmolLM 2 360M Instruct
Shop this upgrade↗

Add a second Intel Arc A770 16GB

~$269

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: 63 new comfortable

  • • Gemma 3 1B
  • • Llama 3.2 1B Instruct
  • • Gemma 4 E2B (Effective 2B)
  • • Llama 3.2 3B 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

Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.

—
Qwen 3.5 235B-A17B (MoE)
397B
qwen
Commercial OK

Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.

—
Qwen 3 235B-A22B
235B
qwen
Commercial OK

Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.

—
Llama 4 Scout
109B
llama
Commercial OK

Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.

—
DeepSeek R1 (671B reasoning)
671B
deepseek
Commercial OK

Even with CPU offload, needs more memory than your VRAM (16 GB) + 60% of system RAM (19 GB) combined.

—

How to read these numbers

M
Measured — we ran this exact combo on owner hardware.

~
Extrapolated — predicted from a measured benchmark on similar-bandwidth hardware.

E
Estimated — pure formula based on VRAM bandwidth and model architecture.

Full methodology →

Want a specific benchmark we don't have? Email support@runlocalai.co and we'll prioritize it.