RUNLOCALAIv38
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RUNLOCALAI · v38
Will it run? / Intel Arc A770 16GB

What can Intel Arc A770 16GB run?

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
186 models

Full-VRAM resident, with room for context. No compromises.

#1all-MiniLM-L6-v2
0.022B
other
Commercial OK
Quant: Q4_K_MContext: 256VRAM: 1.0 GBHeadroom: 15.0 GB
18938
tok/s
Estimated
Weights
0.01 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
1.00 GB
Model details →
#2Piper
0.025B
other
Commercial OK
Quant: Q4_K_MContext: 0VRAM: 1.0 GBHeadroom: 15.0 GB
16666
tok/s
Estimated
Weights
0.02 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
1.00 GB
Model details →
#3Whisper Tiny
0.039B
other
Commercial OK
Quant: Q4_K_MContext: 30VRAM: 1.0 GBHeadroom: 15.0 GB
10683
tok/s
Estimated
Weights
0.02 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
1.00 GB
Model details →
#4Whisper Base
0.074B
other
Commercial OK
Quant: Q4_K_MContext: 30VRAM: 1.0 GBHeadroom: 15.0 GB
5630
tok/s
Estimated
Weights
0.04 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
1.00 GB
Model details →
#5Kokoro 82M
0.082B
other
Commercial OK
Quant: Q4_K_MContext: 0VRAM: 1.1 GBHeadroom: 14.9 GB
5081
tok/s
Estimated
Weights
0.05 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
1.00 GB
Model details →
#6all-mpnet-base-v2
0.109B
other
Commercial OK
Quant: Q4_K_MContext: 384VRAM: 1.1 GBHeadroom: 14.9 GB
3822
tok/s
Estimated
Weights
0.07 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
1.00 GB
Model details →
#7paraphrase-multilingual-MiniLM-L12-v2
0.118B
other
Commercial OK
Quant: Q4_K_MContext: 128VRAM: 1.1 GBHeadroom: 14.9 GB
3531
tok/s
Estimated
Weights
0.07 GB
KV cache
0.00 GB
Activations
0.00 GB
Runtime
1.00 GB
Model details →
#8Nomic Embed Text v1.5
0.137B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 1.2 GBHeadroom: 14.8 GB
3041
tok/s
Estimated
Weights
0.08 GB
KV cache
0.07 GB
Activations
0.01 GB
Runtime
1.00 GB
Model details →
#9SmolLM2 135M Instruct
0.135B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 1.2 GBHeadroom: 14.8 GB
3086
tok/s
Estimated
Weights
0.08 GB
KV cache
0.07 GB
Activations
0.01 GB
Runtime
1.00 GB
Model details →
#10GTE ModernBERT Base
0.149B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 1.2 GBHeadroom: 14.8 GB
2796
tok/s
Estimated
Weights
0.09 GB
KV cache
0.07 GB
Activations
0.01 GB
Runtime
1.00 GB
Model details →
#11Whisper Small
0.244B
other
Commercial OK
Quant: Q4_K_MContext: 30VRAM: 1.2 GBHeadroom: 14.8 GB
1708
tok/s
Estimated
Weights
0.15 GB
KV cache
0.00 GB
Activations
0.01 GB
Runtime
1.00 GB
Model details →
#12Gemma 3 270M
0.27B
gemma
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 1.3 GBHeadroom: 14.7 GB
1543
tok/s
Estimated
Weights
0.16 GB
KV cache
0.14 GB
Activations
0.02 GB
Runtime
1.00 GB
Model details →

Runs with tradeoffs
65 models

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

Qwen 3 30B-A3B
30B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 35.0 GBHeadroom: 0.2 GB
  • • Partial CPU offload: ~54% of layers run on CPU
ollama run qwen3:30b
14
tok/s
Estimated
Weights
18.11 GB
KV cache
15.00 GB
Activations
0.91 GB
Runtime
1.00 GB
Model details →
Qwen 2.5 Coder 32B Instruct
32B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 23.4 GBHeadroom: 11.8 GB
  • • Partial CPU offload: ~32% of layers run on CPU
ollama run qwen2.5-coder:32b
13
tok/s
Estimated
Weights
19.32 GB
KV cache
2.15 GB
Activations
0.97 GB
Runtime
1.00 GB
Model details →
Gemma 4 31B Dense
31B
gemma
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 24.5 GBHeadroom: 10.7 GB
  • • Partial CPU offload: ~35% of layers run on CPU
ollama run gemma4:31b
13
tok/s
Estimated
Weights
18.72 GB
KV cache
3.88 GB
Activations
0.94 GB
Runtime
1.00 GB
Model details →
Qwen 3 32B
32B
qwen
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 25.3 GBHeadroom: 9.9 GB
  • • Partial CPU offload: ~37% of layers run on CPU
ollama run qwen3:32b
13
tok/s
Estimated
Weights
19.32 GB
KV cache
4.00 GB
Activations
0.97 GB
Runtime
1.00 GB
Model details →
Qwen 3 8B
8B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 13.9 GBHeadroom: 2.1 GB
  • • Tight VRAM fit — only 2.1 GB headroom left for context growth
ollama run qwen3:8b
30
tok/s
Estimated
Weights
8.50 GB
KV cache
4.00 GB
Activations
0.43 GB
Runtime
1.00 GB
Model details →
DeepSeek R1 Distill Qwen 32B
32B
deepseek
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 25.3 GBHeadroom: 9.9 GB
  • • Partial CPU offload: ~37% of layers run on CPU
ollama run deepseek-r1:32b
13
tok/s
Estimated
Weights
19.32 GB
KV cache
4.00 GB
Activations
0.97 GB
Runtime
1.00 GB
Model details →
Gemma 4 26B MoE
26B
gemma
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 30.5 GBHeadroom: 4.7 GB
  • • Partial CPU offload: ~48% of layers run on CPU
ollama run gemma4:26b-moe
16
tok/s
Estimated
Weights
15.70 GB
KV cache
13.00 GB
Activations
0.79 GB
Runtime
1.00 GB
Model details →
Nemotron 3 Nano (30B-A3B)
30B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 35.0 GBHeadroom: 0.2 GB
  • • Partial CPU offload: ~54% of layers run on CPU
ollama run nemotron3:nano
14
tok/s
Estimated
Weights
18.11 GB
KV cache
15.00 GB
Activations
0.91 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: 82 new tradeoff

  • • Qwen 3 30B-A3B
  • • Llama 3.3 70B Instruct
  • • Qwen 2.5 Coder 32B Instruct
  • • Gemma 4 31B Dense
Shop this upgrade↗

Upgrade to Intel Arc Pro B60 24GB

see current pricing

24 GB VRAM (vs your 16 GB) plus a bandwidth jump from ~559 GB/s to ~456 GB/s.

Unlocks: 28 new comfortable

  • • DeepSeek V2 Lite Chat
  • • DeepSeek R1 Distill Qwen 7B
  • • Qwen 3 8B
  • • Hermes 3 Llama 3.1 8B
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: 50 new comfortable

  • • DeepSeek V2 Lite Chat
  • • DeepSeek R1 Distill Qwen 7B
  • • Qwen 3 8B
  • • Hermes 3 Llama 3.1 8B
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.

—
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.

—
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.

—

How to read these numbers

Measured here
Measured here - RunLocalAI ran this exact combo on owner hardware with public evidence.

Source-backed
Source-backed / community - a reproduced public source supports the speed, but it is not labeled as owner-measured.

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

Estimated
Estimated - formula based on VRAM bandwidth and model architecture; not a benchmark row.

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