RTX PRO 4500 Blackwell
RTX PRO 4500 Blackwell has 32 GB of VRAM at 896 GB/s — about 29.76 GiB usable after driver and compositor overhead. 2024 of 2118 indexed models fit at 8K context with q4_0 KV.
What fits at 8K context
| Model | Best quant | Params | Weights● | KV● | Total in memory◐ | Headroom◐ | tok/s◐ |
|---|---|---|---|---|---|---|---|
| Bernini-R | Q8_0 | 14.3B | 28.71 GiB | 0.00 GiB | 29.76 GiB | 0.00 GiB | 18±22% |
| CalmeRys-78B-Orpo-v0.1 | I1-IQ2_S | 78.0B | 27.87 GiB | 0.76 GiB | 29.76 GiB | 0.00 GiB | 18±22% |
| Huihui-Qwen3-Coder-Next-abliteratedMoE | I1-IQ3_XXS | 79.7B | 28.68 GiB | 0.05 GiB | 29.72 GiB | 0.04 GiB | 119±37% |
| Salience-1.5-ProMoE | Q6_K_L | 36.0B | 28.66 GiB | 0.04 GiB | 29.71 GiB | 0.05 GiB | 106±37% |
| Qwable-v1MoE | Q6_K_L | 36.0B | 28.66 GiB | 0.04 GiB | 29.71 GiB | 0.05 GiB | 106±37% |
| T-SearchMoE | Q6_K_L | 36.0B | 28.66 GiB | 0.04 GiB | 29.71 GiB | 0.05 GiB | 106±37% |
| CodeLlama-70b-Instruct-hf | I1-IQ3_S | 69.0B | 27.86 GiB | 0.70 GiB | 29.69 GiB | 0.07 GiB | 18±22% |
| CodeLlama-70b-Python-hf | I1-IQ3_S | 69.0B | 27.86 GiB | 0.70 GiB | 29.69 GiB | 0.07 GiB | 18±22% |
| Nous-Hermes-Llama2-70b | I1-IQ3_S | 69.0B | 27.86 GiB | 0.70 GiB | 29.69 GiB | 0.07 GiB | 18±22% |
| Midnight-Miqu-70B-v1.5 | I1-IQ3_S | 69.0B | 27.86 GiB | 0.70 GiB | 29.69 GiB | 0.07 GiB | 18±22% |
| KafkaLM-70B-German-V0.1 | Q3_K_S | 69.0B | 27.86 GiB | 0.70 GiB | 29.69 GiB | 0.07 GiB | 18±22% |
| llama2_70b_chat_uncensored | Q3_K_S | 69.0B | 27.86 GiB | 0.70 GiB | 29.69 GiB | 0.07 GiB | 18±22% |
| Xwin-LM-70b-V0.1 | Q3_K_S | 69.0B | 27.86 GiB | 0.70 GiB | 29.69 GiB | 0.07 GiB | 18±22% |
| Llama-2-70b-chat-hf | Q3_K_S | 69.0B | 27.86 GiB | 0.70 GiB | 29.69 GiB | 0.07 GiB | 18±22% |
| uyu-2-28B | Q8_0 | 28.2B | 27.92 GiB | 0.68 GiB | 29.69 GiB | 0.07 GiB | 18±22% |
| Seed-OSS-36B-Instruct | Q6_K_L | 36.2B | 27.99 GiB | 0.56 GiB | 29.65 GiB | 0.11 GiB | 18±22% |
| Hermes-4.3-36B | Q6_K_L | 36.2B | 27.99 GiB | 0.56 GiB | 29.65 GiB | 0.11 GiB | 18±22% |
| Melody1437-27B | Q3_K_M | 27.8B | 28.40 GiB | 0.14 GiB | 29.61 GiB | 0.15 GiB | 18±22% |
| Rombo-LLM-V3.0-Qwen-72b | I1-Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Qwen2.5-72B-Instruct-abliterated | I1-Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Qwen2.5-72B-Instruct-abliterated-v2 | I1-Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| HuatuoGPT-o1-72B | Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| MiroThinker-v1.0-72B | I1-Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| EVA-Qwen2.5-72B-v0.2 | Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Qwen2.5-Math-72B-Instruct | Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Qwen2.5-72B-Instruct | Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Malaysian-Qwen2.5-72B-Instruct | I1-Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Qwen2.5-72B | I1-Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| magnum-v4-72b | I1-Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| KAT-Dev-72B-Exp | Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Homer-v1.0-Qwen2.5-72B | Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Qwen2.5-VL-72B-Instruct | Q2_K | 73.4B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Chuluun-Qwen2.5-72B-v0.01 | Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Tower-Plus-72B-ultra-uncensored-heretic | I1-Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Chronos-Platinum-72B | Q2_K | 72.7B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| UI-TARS-72B-DPO | Q2_K | 73.4B | 27.76 GiB | 0.70 GiB | 29.60 GiB | 0.16 GiB | 18±22% |
| Qwen2.5-7B-Instruct-1M | F32 | 7.6B | 28.38 GiB | 0.12 GiB | 29.55 GiB | 0.21 GiB | 18±22% |
| DeepSeek-R1-Distill-Qwen-7B | F32 | 7.6B | 28.38 GiB | 0.12 GiB | 29.55 GiB | 0.21 GiB | 18±22% |
| UI-TARS-7B-DPO | F32 | 8.3B | 28.38 GiB | 0.12 GiB | 29.55 GiB | 0.21 GiB | 18±22% |
| Qwen2-7B-Instruct | F32 | 7.6B | 28.38 GiB | 0.12 GiB | 29.55 GiB | 0.21 GiB | 18±22% |
| Hercules-5.0-Qwen2-7B | F32 | 7.6B | 28.38 GiB | 0.12 GiB | 29.55 GiB | 0.21 GiB | 18±22% |
| Gemma-3-27B-MeditronFO | Q8_0 | 28.8B | 28.13 GiB | 0.35 GiB | 29.55 GiB | 0.21 GiB | 18±22% |
| Kepler-8B-Instruct-v2 | F16 | 7.6B | 28.37 GiB | 0.12 GiB | 29.55 GiB | 0.21 GiB | 18±22% |
| MiniCPM-o-2_6 | F32 | 8.7B | 28.37 GiB | 0.12 GiB | 29.54 GiB | 0.22 GiB | 18±22% |
| Llama-4-Scout-17B-16E-InstructMoEKV unresolved | IQ2_XXS | 109B | 28.09 GiB | 0.42 GiB | 29.54 GiB | 0.22 GiB | 75±37% |
| Devstral-2-123B-Instruct-2512 | IQ1_M | 125B | 27.59 GiB | 0.77 GiB | 29.52 GiB | 0.24 GiB | 18±22% |
| Mistral-Medium-3.5-128B | I1-IQ1_M | 128B | 27.59 GiB | 0.77 GiB | 29.52 GiB | 0.24 GiB | 18±22% |
| XORTRON-NXTXPRTXXL | I1-IQ1_M | 128B | 27.59 GiB | 0.77 GiB | 29.52 GiB | 0.24 GiB | 18±22% |
| Qwen3-72B-Synthesis | Q2_K | 72.7B | 27.68 GiB | 0.70 GiB | 29.52 GiB | 0.24 GiB | 18±22% |
| Qwen3-53B-A3B-2507-THINKING-TOTAL-RECALL-v2-MASTER-CODERMoE | I1-Q4_K_S | 53.0B | 28.13 GiB | 0.37 GiB | 29.50 GiB | 0.26 GiB | 69±37% |
| Apertus-70B-Instruct-2509 | IQ3_XS | 70.6B | 27.55 GiB | 0.70 GiB | 29.44 GiB | 0.32 GiB | 18±22% |
| Llama-3_3-Nemotron-Super-49B-v1_5 | Q3_K_M | 49.9B | 22.64 GiB | 5.63 GiB | 29.41 GiB | 0.35 GiB | 18±22% |
| Valkyrie-49B-v2.1 | I1-Q3_K_M | 49.9B | 22.64 GiB | 5.63 GiB | 29.41 GiB | 0.35 GiB | 18±22% |
| Llama-3_3-Nemotron-Super-49B-v1 | Q3_K_M | 49.9B | 22.64 GiB | 5.63 GiB | 29.41 GiB | 0.35 GiB | 18±22% |
| Kimi-Dev-72B | UD-IQ2_M | 72.7B | 27.56 GiB | 0.70 GiB | 29.40 GiB | 0.36 GiB | 18±22% |
| Snowpiercer-15B-v4 | BF16 | 15.0B | 27.90 GiB | 0.44 GiB | 29.39 GiB | 0.37 GiB | 18±22% |
| Qwen3.5-88BMoE | I1-Q2_K_S | 87.7B | 28.30 GiB | 0.05 GiB | 29.38 GiB | 0.38 GiB | 95±37% |
| WizardLM-Uncensored-SuperCOT-StoryTelling-30b | Q6_K | 32.5B | 24.85 GiB | 3.43 GiB | 29.35 GiB | 0.41 GiB | 18±22% |
| Wizard-Vicuna-30B-Uncensored | I1-Q6_K | 32.5B | 24.85 GiB | 3.43 GiB | 29.35 GiB | 0.41 GiB | 18±22% |
| archangel_sft-kto_llama30b | I1-Q6_K | 32.5B | 24.85 GiB | 3.43 GiB | 29.35 GiB | 0.41 GiB | 18±22% |
Speed is modeled, not measured: decode is memory-bandwidth bound, so tokens per second is bytes read per token against achievable bandwidth. Mixture-of-experts models carry a wider band because only the routed experts are read each step, and few have been measured publicly.
Measured on this card
| Workload◍ | Median | Middle 50% | Runs |
|---|---|---|---|
| Prompt processing | 4623.70 tok/s | 3136.07–6649.93 | 24 |
| Text generation | 155.65 tok/s | 81.58–169.65 | 20 |
Aggregated from community-submitted runs, so the spread is wide by nature — it covers different models, resolutions, step counts and settings, not one controlled configuration. Read the middle 50% rather than the median alone. These figures are reproduced with attribution from llama.cpp-discussion-15013.
Questions people ask
- What AI models can a RTX PRO 4500 Blackwell run?
- 2024 of 2118 indexed open-weight models fit a RTX PRO 4500 Blackwell at 8,192 context with q4_0 KV cache, the largest being Bernini-R at Q8_0. That covers text, vision-language, image, video and speech models.
- How much usable memory does a RTX PRO 4500 Blackwell actually have?
- Its nameplate is 32 GB, but about 29.76 GiB is available to a model once driver and compositor overhead is accounted for.
- Is a RTX PRO 4500 Blackwell fast for local AI?
- Its memory bandwidth is 896 GB/s, and that figure — not teraflops — is what governs token generation speed. Capacity decides what you can run; bandwidth decides how fast it runs.