NVIDIA · Blackwell
Best AI Models for NVIDIA RTX PRO 4500 Blackwell Server Edition (32 GB)
Runs 27–31B and 35B MoE models well; 70B doesn't fit in 32 GB.
Passive single-slot server card — needs chassis airflow. Same 32 GB and 10,496 cores as the Workstation Edition but 800 GB/s at 165 W rather than 896 GB/s at 200 W.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 29.9 t/s | 29.9 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 29.9 t/s | 29.9 tok/s | Q4_K_M · 17.9 GB | |
| 3 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 25.5 t/s | 25.5 tok/s | Q4_K_M · 21.7 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 144 t/s | 144 tok/s | Q4_K_M · 16.5 GB | |
| 5 | Q4_K_M · 19.3 GB · 177 t/s | 177 tok/s | Q4_K_M · 19.3 GB |
| # | Model | Speed | Coding Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 29.9 t/s | 29.9 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 25.5 t/s | 25.5 tok/s | Q4_K_M · 21.7 GB | |
| 3 | Qwen3.6 35B A3BAlibaba Q4_K_M · 22.0 GB · 129 t/s | 129 tok/s | Q4_K_M · 22.0 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 144 t/s | 144 tok/s | Q4_K_M · 16.5 GB | |
| 5 | Q4_K_M · 19.3 GB · 177 t/s | 177 tok/s | Q4_K_M · 19.3 GB |
| # | Model | Speed | Reasoning Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 29.9 t/s | 29.9 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 25.5 t/s | 25.5 tok/s | Q4_K_M · 21.7 GB | |
| 3 | Qwen3.5 27BAlibaba Q4_K_M · 17.9 GB · 29.9 t/s | 29.9 tok/s | Q4_K_M · 17.9 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 144 t/s | 144 tok/s | Q4_K_M · 16.5 GB | |
| 5 | Q4_K_M · 19.3 GB · 177 t/s | 177 tok/s | Q4_K_M · 19.3 GB |
| # | Model | Speed | Math Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 29.9 t/s | 29.9 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 29.9 t/s | 29.9 tok/s | Q4_K_M · 17.9 GB | |
| 3 | Qwen3.6 35B A3BAlibaba Q4_K_M · 22.0 GB · 129 t/s | 129 tok/s | Q4_K_M · 22.0 GB | |
| 4 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 25.5 t/s | 25.5 tok/s | overall | Q4_K_M · 21.7 GB |
| 5 | Q4_K_M · 19.3 GB · 177 t/s | 177 tok/s | Q4_K_M · 19.3 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 160 t/s | 160 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Q4_K_M · 19.3 GB · 177 t/s | 177 tok/s | Q4_K_M · 19.3 GB | |
| 3 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 159 t/s | 159 tok/s | Q4_K_M · 13.1 GB | |
| 4 | Qwen3 30B A3B Thinking 2507Alibaba Q4_K_M · 19.4 GB · 152 t/s | 152 tok/s | Q4_K_M · 19.4 GB | |
| 5 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 144 t/s | 144 tok/s | Q4_K_M · 16.5 GB |
| # | Model | Speed | Vision Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 29.9 t/s | 29.9 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 29.9 t/s | 29.9 tok/s | Q4_K_M · 17.9 GB | |
| 3 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 25.5 t/s | 25.5 tok/s | Q4_K_M · 21.7 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 144 t/s | 144 tok/s | Q4_K_M · 16.5 GB | |
| 5 | MiniCPM V 4.7 35B A3BOpenBMB Q4_K_M · 22.1 GB · 145 t/s | 145 tok/s | Q4_K_M · 22.1 GB |
The RTX PRO 4500 Blackwell Server Edition runs 27–31B and 35B MoE models well. Blackwell generation, released 2026.
RTX PRO 4500 Blackwell Server Edition strengths and weaknesses
Strengths
- Runs 35B MoE models: Qwen3.6 35B A3B at 129 tok/s in 22 GB
- Room for long context: Qwen3.8 27B at Q4 uses 17.9 GB, leaving 14.1 GB free
- Reads long prompts fast: A 4K-token prompt on Qwen3.8 27B starts answering in 2.5 s
- FP8 and NVFP4 run natively: Blackwell takes FP8 and NVFP4 checkpoints in vLLM as published
Weaknesses
- 70B models don't fit: Llama 3.3 70B Instruct needs 51.3 GB at Q4 vs 32 GB here
Output speed depends on memory bandwidth (800 GB/s). Grey rows need more than 32 GB.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB81.8tok/s
- 14BQwen3 14B · Q4_K_M · 11.9 GB54.7tok/s
- 27–31BQwen3.8 27B · Q4_K_M · 17.9 GB29.9tok/s
- 35B MoEQwen3.6 35B A3B · Q4_K_M · 22.0 GB129tok/s
- 70BLlama 3.3 70B Instruct · not at 4-bitneeds 51.3 GB
- 120B MoEGPT OSS 120B · not at 4-bitneeds 70.8 GB
Estimated speeds: Q4_K_M, 4K context, one user. How we estimate
All 1176 models on the RTX PRO 4500 Blackwell Server Edition
Featured onlyBest quant that fits, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
| Q4_K_M | 1.7 GB | 406.3 t/s | 33K | S100, Runs great | ||
| BF16 | 1.6 GB | 852.5 t/s | — | S100, Runs great | ||
| Q4_K_M | 6.8 GB | 105.9 t/s | 33K | S92, Runs great | ||
Nemotron H 8B Reasoning 128KChatReasoning | BF16 | 20.4 GB | 29.2 t/s | — | A70, Runs well | |
Meta Llama 3 8BChat | Q4_K_M | 6.2 GB | 96.5 t/s | 8K | S90, Runs great | |
Qwen2.5 0.5BChatFunctions | Q4_K_M | 0.8 GB | 838.7 t/s | 33K | S100, Runs great | |
| Q4_K_M | 5.0 GB | 112.6 t/s | 4K | S94, Runs great | ||
Qwen3 14B BaseChat | Q4_K_M | 11.8 GB | 54.7 t/s | 33K | A81, Runs well | |
CodeQwen1.5 7BChatCode | Q4_K_M | 5.7 GB | 108.8 t/s | 66K | S93, Runs great | |
Yi 9BChat | Q4_K_M | 6 GB | 89.7 t/s | 4K | S89, Runs great | |
Xgen 7B 8k BaseChat | Q4_K_M | 5.7 GB | 112.6 t/s | 8K | S94, Runs great | |
| BF16 | 17.9 GB | 29.6 t/s | 4K | A70, Runs well | ||
BioMistral 7BChat | Q4_K_M | 6.7 GB | 109.0 t/s | 33K | S93, Runs great | |
Yi 6B ChatChat | Q4_K_M | 4.2 GB | 127.8 t/s | 4K | S95, Runs great | |
Baichuan 7BChat | Q4_K_M | 5.0 GB | 112.6 t/s | 4K | S94, Runs great |
Rent NVIDIA RTX PRO 4500 Blackwell Server Edition in the cloud
Hourly rate on demand for one RTX PRO 4500 Blackwell Server Edition.
RunPod$5+ bonus credit
from$0.72/hr
Cost per million tokens
Output-token cost on an RTX PRO 4500 Blackwell Server Edition rented at $0.72/hr, one request at a time. Batch several users on the same card and the cost per token drops several-fold.
| Model | Quant | Speed | Per 1M output |
|---|---|---|---|
| NVIDIA Nemotron 3.5 Lightning 30B A3B BF16 | 177 tok/s | $1.13$0.010 input | |
| Gemma 4 26B A4B IT | 144 tok/s | $1.39$0.019 input | |
| Qwen3.6 35B A3B | 129 tok/s | $1.55$0.021 input | |
| Qwen3.8 27B | 30 tok/s | $6.69$0.12 input | |
| Muse Glimmer 30B | 28 tok/s | $7.04$0.13 input |
Specs
- Architecture
- Blackwell
- VRAM
- 32 GB GDDR7
- Memory bandwidth
- 800.0 GB/s
- FP16 (dense)
- 203.00 TFLOPS
- CUDA cores
- 10,496
- Tensor cores
- 328
- Compute capability
- 12.0
- TDP
- 165 W
- Released
- 2026-03-01
RTX PRO 4500 Blackwell Server Edition FAQ
What is the largest model the RTX PRO 4500 Blackwell Server Edition can run?
Qwen3.6 35B A3B (36.0B) is the largest at 4-bit or better: at Q4_K_M it uses 22.0 GB of 32 GB, and runs at about 129 tok/s.
Can the RTX PRO 4500 Blackwell Server Edition run Qwen3.8 27B?
Yes. Qwen3.8 27B fits at Q4_K_M, using 17.9 GB of 32 GB, and it is the best model that runs well on this card.
Can the RTX PRO 4500 Blackwell Server Edition run 70B models?
No. Llama 3.3 70B Instruct needs 51.3 GB at Q4, more than the 32 GB on this card.
How many tokens per second does the RTX PRO 4500 Blackwell Server Edition give?
About 29.9 tok/s on Qwen3.8 27B at Q4_K_M, with the first token after 2.5 s on a 4K-token prompt.
What power supply does the RTX PRO 4500 Blackwell Server Edition need?
Plan a 350 W PSU (2× the 165 W TDP).
Is 32 GB enough for coding and agents?
Yes for coding: Qwen3.8 27B, the best of the 10 coding models that fit, runs at about 30 tok/s. For agents, not yet: no agent-scored model fits in less than 96 GB.