What can NVIDIA GeForce RTX 5090 run for reasoning?

Build: NVIDIA GeForce RTX 5090 + — + 32 GB RAM (windows)

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

Runs comfortably
152 models

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

#1DeepSeek R1 Distill Qwen 7B
7B
deepseek
Commercial OK
Quant: Q8_0Context: 8,192VRAM: 13.8 GBHeadroom: 18.2 GBTTFT: fast
ollama run deepseek-r1:7b
157
tok/s
Estimated
Weights
8.10 GB
KV cache
3.50 GB
Activations
0.41 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~143 ms (fast)
#2Phi-4 Reasoning 14B
14B
phi
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 17.6 GBHeadroom: 14.4 GBTTFT: fast
ollama run phi4-reasoning:14b
138
tok/s
Estimated
Weights
8.40 GB
KV cache
7.00 GB
Activations
0.43 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~287 ms (fast)
#3DeepSeek R1 Distill Qwen 14B
14B
deepseek
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 17.6 GBHeadroom: 14.4 GBTTFT: fast
ollama run deepseek-r1:14b
138
tok/s
Estimated
Weights
8.40 GB
KV cache
7.00 GB
Activations
0.43 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~287 ms (fast)
#4Llama 3.1 Nemotron Nano 8B
8B
llama
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 11.0 GBHeadroom: 21.0 GBTTFT: fast
241
tok/s
Estimated
Weights
4.90 GB
KV cache
4.00 GB
Activations
0.25 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~164 ms (fast)
Quant: Q4_K_MContext: 8,192VRAM: 11.6 GBHeadroom: 20.4 GBTTFT: fast
214
tok/s
Estimated
Weights
5.00 GB
KV cache
4.50 GB
Activations
0.26 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~184 ms (fast)
#6RefinedNeuro RN TR R1
8B
llama
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 11.0 GBHeadroom: 21.0 GBTTFT: fast
ollama run RefinedNeuro/RN_TR_R1:latest
241
tok/s
Estimated
Weights
4.90 GB
KV cache
4.00 GB
Activations
0.25 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~164 ms (fast)
#7DeepSeek R1 Distill Llama 8B
8B
deepseek
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 10.7 GBHeadroom: 21.3 GBTTFT: fast
241
tok/s
Estimated
Weights
4.70 GB
KV cache
4.00 GB
Activations
0.24 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~164 ms (fast)
Quant: Q4_K_MContext: 2,048VRAM: 23.6 GBHeadroom: 8.4 GBTTFT: noticeable
62
tok/s
Estimated
Weights
17.10 GB
KV cache
3.88 GB
Activations
0.86 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~635 ms (noticeable)
#9DeepSeek R1 Distill Qwen 32B
32B
deepseek
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 25.8 GBHeadroom: 6.2 GBTTFT: noticeable
ollama run deepseek-r1:32b
60
tok/s
Estimated
Weights
19.00 GB
KV cache
4.00 GB
Activations
0.95 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~655 ms (noticeable)
#10QwQ 32B Preview
32B
qwen
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 25.8 GBHeadroom: 6.2 GBTTFT: noticeable
ollama run qwq:32b
60
tok/s
Estimated
Weights
19.00 GB
KV cache
4.00 GB
Activations
0.95 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~655 ms (noticeable)
#11EXAONE 4.0.1 32B
32B
exaone
Quant: Q4_K_MContext: 2,048VRAM: 24.3 GBHeadroom: 7.7 GBTTFT: noticeable
60
tok/s
Estimated
Weights
17.60 GB
KV cache
4.00 GB
Activations
0.88 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~655 ms (noticeable)
#12Qwen3 Swallow 32B RL v0.2
32B
qwen
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 24.3 GBHeadroom: 7.7 GBTTFT: noticeable
60
tok/s
Estimated
Weights
17.60 GB
KV cache
4.00 GB
Activations
0.88 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~655 ms (noticeable)

Runs with tradeoffs
26 models

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

DeepSeek R1 Distill Mistral 24B
24B
deepseek
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 28.5 GBHeadroom: 3.5 GBTTFT: fast
  • Tight VRAM fit — only 3.5 GB headroom left for context growth
80
tok/s
Estimated
Weights
14.00 GB
KV cache
12.00 GB
Activations
0.71 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~492 ms (fast)
Hermes 4 70B FP8
70B
llama
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 51.0 GBHeadroom: 0.2 GBTTFT: noticeable
  • Partial CPU offload: ~37% of layers run on CPU
28
tok/s
Estimated
Weights
38.50 GB
KV cache
8.75 GB
Activations
1.93 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~1434 ms (noticeable)
Nemotron 3 Nano Omni 33B
33B
other
Commercial OK
Quant: Q4_K_MContext: 8,192VRAM: 47.7 GBHeadroom: 3.5 GBTTFT: noticeable
  • Partial CPU offload: ~33% of layers run on CPU
ollama run nemotron3:33b
58
tok/s
Estimated
Weights
28.00 GB
KV cache
16.50 GB
Activations
1.41 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~676 ms (noticeable)
Nemotron 3 Super 49B
49B
other
Commercial OK
Quant: AWQ-INT4Context: 2,048VRAM: 37.3 GBHeadroom: 13.9 GBTTFT: noticeable
  • Partial CPU offload: ~14% of layers run on CPU
24
tok/s
Estimated
Weights
28.00 GB
KV cache
6.13 GB
Activations
1.40 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~1004 ms (noticeable)
Jamba 1.5 Mini
52B
other
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 39.8 GBHeadroom: 11.4 GBTTFT: fast
  • Partial CPU offload: ~20% of layers run on CPU
161
tok/s
Estimated
Weights
30.00 GB
KV cache
6.50 GB
Activations
1.50 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~246 ms (fast)
Pollux Judge 32B
32B
other
Commercial OK
Quant: Q4_K_MContext: 4,096VRAM: 28.3 GBHeadroom: 3.7 GBTTFT: noticeable
  • Tight VRAM fit — only 3.7 GB headroom left for context growth
60
tok/s
Estimated
Weights
17.60 GB
KV cache
8.00 GB
Activations
0.88 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~655 ms (noticeable)
Qwen3.6 35B-A3B
35B
qwen
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 31.4 GBHeadroom: 0.6 GBTTFT: noticeable
  • Tight VRAM fit — only 0.6 GB headroom left for context growth
ollama run qwen3.6:35b-a3b
55
tok/s
Estimated
Weights
24.00 GB
KV cache
4.38 GB
Activations
1.20 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~717 ms (noticeable)
Qwen3.5 35B-A3B
35B
qwen
Commercial OK
Quant: Q4_K_MContext: 2,048VRAM: 31.4 GBHeadroom: 0.6 GBTTFT: noticeable
  • Tight VRAM fit — only 0.6 GB headroom left for context growth
ollama run qwen3.5:35b-a3b
55
tok/s
Estimated
Weights
24.00 GB
KV cache
4.38 GB
Activations
1.20 GB
Runtime
1.80 GB
Time to first token (prefill, 512-token prompt): ~717 ms (noticeable)

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: 64 new comfortable, 43 new tradeoff

  • Qwen 3 0.6B
  • Llama 3.2 3B Instruct
  • Qwen 3 1.7B
  • Gemma 3 270M

Upgrade to NVIDIA A100 40GB

see current pricing

40 GB VRAM (vs your 32 GB) plus a bandwidth jump from ~1792 GB/s to ~1555 GB/s.

Unlocks: 85 new comfortable

  • Qwen 3 0.6B
  • Qwen3.6 35B-A3B
  • Llama 3.2 3B Instruct
  • Qwen 3 1.7B

Add a second NVIDIA GeForce RTX 5090

~$2499

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: 103 new comfortable

  • Qwen 3 0.6B
  • Llama 3.3 70B Instruct
  • DeepSeek R1 Distill Llama 70B
  • Qwen3.6 35B-A3B

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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 (32 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 (32 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 (32 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 (32 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 (32 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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