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. 1954 of 2118 indexed models fit at 32K context with f16 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
text 1673vision language 177video 16embedding 26image 2audio tts 21audio asr 39

What fits at 32K context

largest quantization that fits, per model · 1954 of 2118 indexed
ModelBest quantParamsWeightsKVTotal in memoryHeadroomtok/s
grug-27bQ8_027.4B26.70 GiB2.00 GiB29.76 GiB0.00 GiB18±22%
Carnice-V2-27bQ8_027.4B26.70 GiB2.00 GiB29.76 GiB0.00 GiB18±22%
Fara1.5-27BQ8_027.4B26.70 GiB2.00 GiB29.76 GiB0.00 GiB18±22%
Bernini-RQ8_014.3B28.71 GiB0.00 GiB29.76 GiB0.00 GiB18±22%
xLAM-8x7b-rMoEIQ4_NL46.7B24.69 GiB4.00 GiB29.73 GiB0.03 GiB26±37%
Apertus-70B-Instruct-2509UD-IQ2_XXS70.6B18.54 GiB10.00 GiB29.72 GiB0.04 GiB18±22%
Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-MTPIQ3_M27.8B26.65 GiB2.00 GiB29.71 GiB0.05 GiB18±22%
Qwen3.5-27B-HERETIC-Polaris-Advanced-Thinking-Alpha-uncensoredQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.5-27B-Deckard-PKD-Heretic-Uncensored-ThinkingQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.6-27B-Heretic2-ThinkingQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.6-27B-abliteratedQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Webcoda-AI-27BQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
KoQweopus-3.5-27B-experimentalQ8_027.8B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Huihui-Qwen3.6-27B-abliteratedQ8_027.8B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.5-27B-hereticQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Huihui-Qwen3.5-27B-abliteratedQ8_027.8B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.5-Queen-27BQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.5-27B-abliteratedQ8_026.9B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
ThinkingCap-Qwen3.6-27B-hereticQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
MusaCoder-27BQ8_026.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen-Image-BenchQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.5-27B-uncensored-heretic-v1Q8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Bonsai-27B-unpackedQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Ternary-Bonsai-27B-unpackedQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.6-27B-Claude-Opus-Reasoning-Distill-v2-hereticQ8_027.4B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Darwin-28B-REASONQ8_026.9B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Huihui-Qwen3.5-27B-Claude-4.6-Opus-abliteratedQ8_027.8B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.5-27B-Claude-4.6-Opus-Reasoning-DistilledQ8_027.8B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.5-27BQ8_027.8B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Qwen3.5-27B-WebNovel-Writer-zhQ8_026.9B26.63 GiB2.00 GiB29.69 GiB0.07 GiB18±22%
Orca-2-13b-Alpaca-UncensoredI1-IQ2_XS13.0B3.62 GiB25.00 GiB29.67 GiB0.09 GiB18±22%
WizardLM-13B-UncensoredI1-IQ2_XS13.0B3.62 GiB25.00 GiB29.67 GiB0.09 GiB18±22%
WizardCoder-Python-13B-V1.0I1-IQ2_XS13.0B3.62 GiB25.00 GiB29.67 GiB0.09 GiB18±22%
Guanaco-13B-UncensoredI1-IQ2_XS13.0B3.62 GiB25.00 GiB29.67 GiB0.09 GiB18±22%
Open_Gpt4_8x7B_v0.1MoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
dolphin-2.6-mixtral-8x7bMoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
dolphin-2.5-mixtral-8x7bMoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
dolphin-2.7-mixtral-8x7bMoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
Nous-Hermes-2-Mixtral-8x7B-DPOMoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
Mixtral-8x7B-v0.1MoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
Mixtral-8x7B-Instruct-v0.1MoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
Mixtral-8x7B-MoE-RP-StoryMoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
Noromaid-v0.4-Mixtral-Instruct-8x7b-ZlossMoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
Open_Gpt4_8x7B_v0.2MoEQ4_046.7B24.63 GiB4.00 GiB29.66 GiB0.10 GiB26±37%
Qwen3.6-28BMoEQ8_028.2B28.00 GiB0.63 GiB29.63 GiB0.13 GiB84±37%
Qwen2.5-Coder-14B-InstructQ6_K14.8B22.58 GiB6.00 GiB29.63 GiB0.13 GiB18±22%
Bielik-11B-v2.3-InstructQ8_011.2B22.34 GiB6.25 GiB29.62 GiB0.14 GiB18±22%
Darwin-35B-A3B-OpusMoEQ6_K36.0B27.99 GiB0.63 GiB29.62 GiB0.14 GiB89±37%
Aurora-Code-1MoEQ6_K34.7B27.99 GiB0.63 GiB29.62 GiB0.14 GiB89±37%
grug-35b-v2MoEQ6_K35.1B27.99 GiB0.63 GiB29.62 GiB0.14 GiB89±37%
grug-35bMoEQ6_K35.1B27.99 GiB0.63 GiB29.62 GiB0.14 GiB89±37%
WorldSim-Opus-3.6-35B-A3BMoEQ6_K35.1B27.99 GiB0.63 GiB29.62 GiB0.14 GiB89±37%
Qwen3.6-35B-A3B-AnkoMoEQ6_K35.1B27.99 GiB0.63 GiB29.62 GiB0.14 GiB89±37%
KAT-Coder-V2.5-DevMoEQ6_K34.7B27.99 GiB0.63 GiB29.62 GiB0.14 GiB89±37%
Ornith-1.0-35BMoEQ6_K34.7B27.99 GiB0.63 GiB29.62 GiB0.14 GiB89±37%
Nex-N2-miniMoEQ6_K35.1B27.99 GiB0.63 GiB29.62 GiB0.14 GiB89±37%
Qwen3.5-99BMoEI1-IQ2_S99.0B27.80 GiB0.75 GiB29.58 GiB0.18 GiB82±37%
Qwen3.6-35B-A3BMoEUD-Q6_K36.0B27.95 GiB0.63 GiB29.58 GiB0.18 GiB89±37%
MathCoder2-CodeLlama-7BF166.7B12.55 GiB16.00 GiB29.58 GiB0.18 GiB18±22%
Llama-2-7b-chat-hfF166.7B12.55 GiB16.00 GiB29.58 GiB0.18 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?
1954 of 2118 indexed open-weight models fit a RTX PRO 4500 Blackwell at 32,768 context with f16 KV cache, the largest being grug-27b 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.