NVIDIA · workstation

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.

Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
32 GB
GDDR7
Bandwidth
896 GB/s
256-bit bus
Tensor FP16
dense
TDP
200 W
$2623 MSRP
KV cachef16q8_0q4_0quantizing the KV cache is a ~2× lever on the dominant term at long context
video 16text 1739vision language 181image 2embedding 26audio tts 21audio asr 39

What fits at 8K context

largest quantization that fits, per model · 2024 of 2118 indexed
ModelBest quantParamsWeightsKVTotal in memoryHeadroomtok/s
Bernini-RQ8_014.3B28.71 GiB0.00 GiB29.76 GiB0.00 GiB18±22%
CalmeRys-78B-Orpo-v0.1I1-IQ2_S78.0B27.87 GiB0.76 GiB29.76 GiB0.00 GiB18±22%
Huihui-Qwen3-Coder-Next-abliteratedMoEI1-IQ3_XXS79.7B28.68 GiB0.05 GiB29.72 GiB0.04 GiB119±37%
Salience-1.5-ProMoEQ6_K_L36.0B28.66 GiB0.04 GiB29.71 GiB0.05 GiB106±37%
Qwable-v1MoEQ6_K_L36.0B28.66 GiB0.04 GiB29.71 GiB0.05 GiB106±37%
T-SearchMoEQ6_K_L36.0B28.66 GiB0.04 GiB29.71 GiB0.05 GiB106±37%
CodeLlama-70b-Instruct-hfI1-IQ3_S69.0B27.86 GiB0.70 GiB29.69 GiB0.07 GiB18±22%
CodeLlama-70b-Python-hfI1-IQ3_S69.0B27.86 GiB0.70 GiB29.69 GiB0.07 GiB18±22%
Nous-Hermes-Llama2-70bI1-IQ3_S69.0B27.86 GiB0.70 GiB29.69 GiB0.07 GiB18±22%
Midnight-Miqu-70B-v1.5I1-IQ3_S69.0B27.86 GiB0.70 GiB29.69 GiB0.07 GiB18±22%
KafkaLM-70B-German-V0.1Q3_K_S69.0B27.86 GiB0.70 GiB29.69 GiB0.07 GiB18±22%
llama2_70b_chat_uncensoredQ3_K_S69.0B27.86 GiB0.70 GiB29.69 GiB0.07 GiB18±22%
Xwin-LM-70b-V0.1Q3_K_S69.0B27.86 GiB0.70 GiB29.69 GiB0.07 GiB18±22%
Llama-2-70b-chat-hfQ3_K_S69.0B27.86 GiB0.70 GiB29.69 GiB0.07 GiB18±22%
uyu-2-28BQ8_028.2B27.92 GiB0.68 GiB29.69 GiB0.07 GiB18±22%
Seed-OSS-36B-InstructQ6_K_L36.2B27.99 GiB0.56 GiB29.65 GiB0.11 GiB18±22%
Hermes-4.3-36BQ6_K_L36.2B27.99 GiB0.56 GiB29.65 GiB0.11 GiB18±22%
Melody1437-27BQ3_K_M27.8B28.40 GiB0.14 GiB29.61 GiB0.15 GiB18±22%
Rombo-LLM-V3.0-Qwen-72bI1-Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Qwen2.5-72B-Instruct-abliteratedI1-Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Qwen2.5-72B-Instruct-abliterated-v2I1-Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
HuatuoGPT-o1-72BQ2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
MiroThinker-v1.0-72BI1-Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
EVA-Qwen2.5-72B-v0.2Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Qwen2.5-Math-72B-InstructQ2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Qwen2.5-72B-InstructQ2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Malaysian-Qwen2.5-72B-InstructI1-Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Qwen2.5-72BI1-Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
magnum-v4-72bI1-Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
KAT-Dev-72B-ExpQ2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Homer-v1.0-Qwen2.5-72BQ2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Qwen2.5-VL-72B-InstructQ2_K73.4B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Chuluun-Qwen2.5-72B-v0.01Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Tower-Plus-72B-ultra-uncensored-hereticI1-Q2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Chronos-Platinum-72BQ2_K72.7B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
UI-TARS-72B-DPOQ2_K73.4B27.76 GiB0.70 GiB29.60 GiB0.16 GiB18±22%
Qwen2.5-7B-Instruct-1MF327.6B28.38 GiB0.12 GiB29.55 GiB0.21 GiB18±22%
DeepSeek-R1-Distill-Qwen-7BF327.6B28.38 GiB0.12 GiB29.55 GiB0.21 GiB18±22%
UI-TARS-7B-DPOF328.3B28.38 GiB0.12 GiB29.55 GiB0.21 GiB18±22%
Qwen2-7B-InstructF327.6B28.38 GiB0.12 GiB29.55 GiB0.21 GiB18±22%
Hercules-5.0-Qwen2-7BF327.6B28.38 GiB0.12 GiB29.55 GiB0.21 GiB18±22%
Gemma-3-27B-MeditronFOQ8_028.8B28.13 GiB0.35 GiB29.55 GiB0.21 GiB18±22%
Kepler-8B-Instruct-v2F167.6B28.37 GiB0.12 GiB29.55 GiB0.21 GiB18±22%
MiniCPM-o-2_6F328.7B28.37 GiB0.12 GiB29.54 GiB0.22 GiB18±22%
Llama-4-Scout-17B-16E-InstructMoEKV unresolvedIQ2_XXS109B28.09 GiB0.42 GiB29.54 GiB0.22 GiB75±37%
Devstral-2-123B-Instruct-2512IQ1_M125B27.59 GiB0.77 GiB29.52 GiB0.24 GiB18±22%
Mistral-Medium-3.5-128BI1-IQ1_M128B27.59 GiB0.77 GiB29.52 GiB0.24 GiB18±22%
XORTRON-NXTXPRTXXLI1-IQ1_M128B27.59 GiB0.77 GiB29.52 GiB0.24 GiB18±22%
Qwen3-72B-SynthesisQ2_K72.7B27.68 GiB0.70 GiB29.52 GiB0.24 GiB18±22%
Qwen3-53B-A3B-2507-THINKING-TOTAL-RECALL-v2-MASTER-CODERMoEI1-Q4_K_S53.0B28.13 GiB0.37 GiB29.50 GiB0.26 GiB69±37%
Apertus-70B-Instruct-2509IQ3_XS70.6B27.55 GiB0.70 GiB29.44 GiB0.32 GiB18±22%
Llama-3_3-Nemotron-Super-49B-v1_5Q3_K_M49.9B22.64 GiB5.63 GiB29.41 GiB0.35 GiB18±22%
Valkyrie-49B-v2.1I1-Q3_K_M49.9B22.64 GiB5.63 GiB29.41 GiB0.35 GiB18±22%
Llama-3_3-Nemotron-Super-49B-v1Q3_K_M49.9B22.64 GiB5.63 GiB29.41 GiB0.35 GiB18±22%
Kimi-Dev-72BUD-IQ2_M72.7B27.56 GiB0.70 GiB29.40 GiB0.36 GiB18±22%
Snowpiercer-15B-v4BF1615.0B27.90 GiB0.44 GiB29.39 GiB0.37 GiB18±22%
Qwen3.5-88BMoEI1-Q2_K_S87.7B28.30 GiB0.05 GiB29.38 GiB0.38 GiB95±37%
WizardLM-Uncensored-SuperCOT-StoryTelling-30bQ6_K32.5B24.85 GiB3.43 GiB29.35 GiB0.41 GiB18±22%
Wizard-Vicuna-30B-UncensoredI1-Q6_K32.5B24.85 GiB3.43 GiB29.35 GiB0.41 GiB18±22%
archangel_sft-kto_llama30bI1-Q6_K32.5B24.85 GiB3.43 GiB29.35 GiB0.41 GiB18±22%
From the filePredictedwhat these mean

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

third-party benchmarks, aggregated
WorkloadMedianMiddle 50%Runs
Prompt processing4623.70 tok/s3136.076649.9324
Text generation155.65 tok/s81.58169.6520
Benchmarked· n=24

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.