What can NVIDIA GeForce RTX 4080 run for vision?

Build: NVIDIA GeForce RTX 4080 + — + 32 GB RAM (windows)

Memory: 16 GB VRAM + 32 GB system RAM
Runner: llama.cpp / Ollama (CUDA)

Runs comfortably
14 models

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

#1Gemma 4 E2B (Effective 2B)
2B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 5.1 GBHeadroom: 10.9 GB
ollama run gemma4:e2b
214
tok/s
Estimated
Weights
2.20 GB
KV cache
1.00 GB
Activations
0.12 GB
Runtime
1.80 GB
#2Phi-3.5 Vision
4.2B
phi
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 6.5 GBHeadroom: 9.5 GB
179
tok/s
Estimated
Weights
2.50 GB
KV cache
2.10 GB
Activations
0.13 GB
Runtime
1.80 GB
#3Moondream 2
1.9B
other
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 3.3 GBHeadroom: 12.7 GB
397
tok/s
Estimated
Weights
1.20 GB
KV cache
0.24 GB
Activations
0.06 GB
Runtime
1.80 GB
#4Qwen 2.5-VL 3B
3B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 5.4 GBHeadroom: 10.6 GB
251
tok/s
Estimated
Weights
2.00 GB
KV cache
1.50 GB
Activations
0.11 GB
Runtime
1.80 GB
#5Qwen 2.5-VL 7B
7B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 9.9 GBHeadroom: 6.1 GB
108
tok/s
Estimated
Weights
4.40 GB
KV cache
3.50 GB
Activations
0.23 GB
Runtime
1.80 GB
#6Qwen 2-VL 7B
7B
qwen
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 10.1 GBHeadroom: 5.9 GB
108
tok/s
Estimated
Weights
4.60 GB
KV cache
3.50 GB
Activations
0.24 GB
Runtime
1.80 GB
#7LLaVA 1.6 Mistral 7B
7B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 10.0 GBHeadroom: 6.0 GB
108
tok/s
Estimated
Weights
4.50 GB
KV cache
3.50 GB
Activations
0.23 GB
Runtime
1.80 GB
#8LLaVA-OneVision 7B
7B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 10.0 GBHeadroom: 6.0 GB
108
tok/s
Estimated
Weights
4.50 GB
KV cache
3.50 GB
Activations
0.23 GB
Runtime
1.80 GB
#9Gemma 4 E4B (Effective 4B)
4B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 8.4 GBHeadroom: 7.6 GB
ollama run gemma4:e4b
107
tok/s
Estimated
Weights
4.40 GB
KV cache
2.00 GB
Activations
0.23 GB
Runtime
1.80 GB
#10Gemma 3 4B
4B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 8.4 GBHeadroom: 7.6 GB
ollama run gemma3:4b
107
tok/s
Estimated
Weights
4.40 GB
KV cache
2.00 GB
Activations
0.23 GB
Runtime
1.80 GB
#11MiniCPM-V 2.6 8B
8B
minicpm
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 11.1 GBHeadroom: 4.9 GB
94
tok/s
Estimated
Weights
5.00 GB
KV cache
4.00 GB
Activations
0.26 GB
Runtime
1.80 GB
#12MiniCPM-V 3 8B
8B
minicpm
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 11.1 GBHeadroom: 4.9 GB
94
tok/s
Estimated
Weights
5.00 GB
KV cache
4.00 GB
Activations
0.26 GB
Runtime
1.80 GB

Runs with tradeoffs
14 models

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

Llama 3.2 11B Vision Instruct
11B
llama
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 15.6 GBHeadroom: 0.4 GB
  • • Tight VRAM fit — only 0.4 GB headroom left for context growth
ollama run llama3.2-vision:11b
69
tok/s
Estimated
Weights
7.90 GB
KV cache
5.50 GB
Activations
0.40 GB
Runtime
1.80 GB
Llama 3.2 11B Vision
11B
llama
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 14.1 GBHeadroom: 1.9 GB
  • • Tight VRAM fit — only 1.9 GB headroom left for context growth
69
tok/s
Estimated
Weights
6.50 GB
KV cache
5.50 GB
Activations
0.33 GB
Runtime
1.80 GB
Gemma 3 12B
12B
gemma
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 15.5 GBHeadroom: 0.5 GB
  • • Tight VRAM fit — only 0.5 GB headroom left for context growth
ollama run gemma3:12b
63
tok/s
Estimated
Weights
7.30 GB
KV cache
6.00 GB
Activations
0.37 GB
Runtime
1.80 GB
Pixtral 12B
12B
mistral
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 15.2 GBHeadroom: 0.8 GB
  • • Tight VRAM fit — only 0.8 GB headroom left for context growth
ollama run pixtral:12b
63
tok/s
Estimated
Weights
7.00 GB
KV cache
6.00 GB
Activations
0.36 GB
Runtime
1.80 GB
GLM-4V 9B
13.9B
glm
Quant: Q4_K_MContext: 2,048VRAM: 12.5 GBHeadroom: 3.5 GB
  • • Tight VRAM fit — only 3.5 GB headroom left for context growth
54
tok/s
Estimated
Weights
8.50 GB
KV cache
1.74 GB
Activations
0.43 GB
Runtime
1.80 GB
Phi-4 Multimodal
14B
phi
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
54
tok/s
Estimated
Weights
9.00 GB
KV cache
1.75 GB
Activations
0.45 GB
Runtime
1.80 GB
Trendyol LLM Asure 12B
11.8B
gemma
Commercial OK
Quant: GGUF_UNKNOWNContext: 8,192VRAM: 12.7 GBHeadroom: 3.3 GB
  • • Tight VRAM fit — only 3.3 GB headroom left for context growth
ollama run alibayram/Trendyol-LLM-Asure-12B:latest
39
tok/s
Estimated
Weights
7.30 GB
KV cache
3.22 GB
Activations
0.37 GB
Runtime
1.80 GB
Gemma 4 26B MoE
26B
gemma
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 31.6 GBHeadroom: 3.6 GB
  • • Partial CPU offload: ~49% of layers run on CPU
ollama run gemma4:26b-moe
29
tok/s
Estimated
Weights
16.00 GB
KV cache
13.00 GB
Activations
0.81 GB
Runtime
1.80 GB

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: 83 new comfortable, 78 new tradeoff

  • • Qwen 3 0.6B
  • • Llama 3.1 8B Instruct
  • • Qwen 3 8B
  • • Qwen 3 1.7B

Upgrade to NVIDIA RTX 2080 Ti 22GB (China-mod)

Check the current price

22 GB VRAM (vs your 16 GB) plus a bandwidth jump from ~? GB/s to ~616 GB/s.

Unlocks: 102 new comfortable

  • • Qwen 3 0.6B
  • • Llama 3.1 8B Instruct
  • • Qwen 3 8B
  • • Qwen 3 1.7B

Add a second NVIDIA GeForce RTX 4080

Launch MSRP $1,199 (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: 133 new comfortable

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

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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

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.

—
DeepSeek V4 Flash (284B MoE)
284B
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

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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