RUNLOCALAIv38
→WILL IT RUNBEST GPUCOMPARETROUBLESHOOTSTARTPULSEMODELSHARDWARETOOLSBENCH
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RUNLOCALAI · v38
Will it run? / NVIDIA GB200 NVL72 / chat

What can NVIDIA GB200 NVL72 run for chat?

Build: NVIDIA GB200 NVL72 + — + 32 GB RAM (windows)

Memory: 13824 GB VRAM + 32 GB system RAM
Runner: llama.cpp / Ollama (CUDA)
AnyChatCodingAgentsReasoningVisionLong contextCreative

Runs comfortably
182 models

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

#1Llama 3.2 3B Instruct
3B
llama
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 14.8 GBHeadroom: 13809.2 GB
ollama run llama3.2:3b
1631
tok/s
E
Weights
3.19 GB
KV cache
1.50 GB
Activations
8.35 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#2Mistral 7B Instruct v0.3
7B
mistral
Commercial OK
Quant: Q5_K_MContext: 8,192VRAM: 18.5 GBHeadroom: 13805.5 GB
ollama run mistral:7b
1081
tok/s
E
Weights
4.81 GB
KV cache
3.50 GB
Activations
8.43 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#3Qwen 3 8B
8B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 22.9 GBHeadroom: 13801.1 GB
ollama run qwen3:8b
612
tok/s
E
Weights
8.50 GB
KV cache
4.00 GB
Activations
8.62 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#4Gemma 2 9B Instruct
9B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 24.5 GBHeadroom: 13799.5 GB
ollama run gemma2:9b
544
tok/s
E
Weights
9.56 GB
KV cache
4.50 GB
Activations
8.67 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#5Mistral Nemo 12B Instruct
12B
mistral
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 29.4 GBHeadroom: 13794.6 GB
ollama run mistral-nemo:12b
408
tok/s
E
Weights
12.75 GB
KV cache
6.00 GB
Activations
8.83 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#6Gemma 3 12B
12B
gemma
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 29.4 GBHeadroom: 13794.6 GB
ollama run gemma3:12b
408
tok/s
E
Weights
12.75 GB
KV cache
6.00 GB
Activations
8.83 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#7Llama 3.1 8B Instruct
8B
llama
Commercial OK
Quant: FP16Context: 8,192VRAM: 27.9 GBHeadroom: 13796.1 GB
ollama run llama3.1:8b
325
tok/s
E
Weights
16.00 GB
KV cache
1.07 GB
Activations
8.99 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#8Qwen 3 14B
14B
qwen
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 32.6 GBHeadroom: 13791.4 GB
ollama run qwen3:14b
350
tok/s
E
Weights
14.88 GB
KV cache
7.00 GB
Activations
8.94 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#9Gemma 4 26B MoE
26B
gemma
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 39.5 GBHeadroom: 13784.5 GB
ollama run gemma4:26b-moe
331
tok/s
E
Weights
15.70 GB
KV cache
13.00 GB
Activations
8.98 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#10OLMo 2 32B
32B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 46.3 GBHeadroom: 13777.7 GB
269
tok/s
E
Weights
19.32 GB
KV cache
16.00 GB
Activations
9.16 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#11Mistral Medium 3.5 (675B MoE)
675B
mistral
Quant: Q4_K_MContext: 8,192VRAM: 775.4 GBHeadroom: 13048.6 GB
210
tok/s
E
Weights
407.53 GB
KV cache
337.50 GB
Activations
28.57 GB
Runtime
1.80 GB
Model details →Run-on benchmark page →
#12Mistral Small 3 24B
24B
mistral
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 48.8 GBHeadroom: 13775.2 GB
ollama run mistral-small:24b
204
tok/s
E
Weights
25.50 GB
KV cache
12.00 GB
Activations
9.47 GB
Runtime
1.80 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: 1 new comfortable

  • • SmolLM 2 360M 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 3 popular models

Need more memory than you have. Shown for orientation.

Qwen 3.6 35B-A3B (MTP)
35B
qwen
Commercial OK

Even with CPU offload, needs more memory than your VRAM (13824 GB) + 60% of system RAM (19 GB) combined.

—
Qwen 3.6 27B (MTP)
27B
qwen
Commercial OK

Even with CPU offload, needs more memory than your VRAM (13824 GB) + 60% of system RAM (19 GB) combined.

—
Ring-2.6-1T
1000B
other
Commercial OK

Even with CPU offload, needs more memory than your VRAM (13824 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.