NVIDIA RTX PRO 4500 Blackwell Server Edition (Condensed, ~30% reduction)

The NVIDIA RTX PRO 4500 Blackwell Server Edition is designed for existing enterprise servers. It is a single-slot, passively cooled 165W board with 32GB GDDR7 and full Blackwell features: 5th-gen Tensor Cores with FP4, 4th-gen RT cores, three encoders/decoders, and MIG support to split the GPU into two isolated 16GB partitions. It replaces the L4 as the entry-level RTX PRO server GPU and fits inside 2U PowerEdge, ProLiant, or ThinkSystem servers without extra power or cooling upgrades.

NVIDIA positions this GPU for right-sizing deployments. Most enterprises do not build large AI factories; they operate air-cooled, legacy data centers constrained by rack power limits and need an on-ramp to accelerated computing without new server hardware. It also suits edge environments, matching typical edge workloads and power budgets. The RTX PRO 6000 sits above it with up to 600W power and 96GB memory. The RTX PRO 4500 shares the same Blackwell architecture but cuts specs roughly in half, letting users run smaller models and scale many lightweight tasks without paying for unused headroom.

Target workloads include small LLM inference, vision AI, video analytics, vector search, embedding generation, transcoding, and vGPU 20 virtual workstations. NVIDIA claims over 5× higher throughput than L4 for small/medium model inference and up to 10× for Nemotron models. Launch partners cover edge video, genome sequencing, and AI-RAN base stations. AWS built its G7 cloud instances on this GPU as a replacement for G6.

Earlier testing inside an HPE ProLiant DL145 Gen11 showed the RTX PRO 4500 delivered 2.7× the throughput of the L4. This review benchmarks it against the 350W dual-slot L40S (mainstream inference GPU for two years) and the RTX PRO 6000, comparing memory and power tradeoffs. Tests ran on a Dell PowerEdge R770, with the RTX PRO 6000 tested at its default 600W and a 450W power cap matching the R770 GPU slot limit. vLLM online serving tests used four models across two context lengths.

Brief preview: At typical chat/agent context lengths, the 165W RTX PRO 4500 matches L40S performance on FP8/BF16 models using less than half the power. Its 32GB frame buffer becomes a bottleneck at 8K input. On this vLLM build, Blackwell’s flagship NVFP4 precision performs similarly across the tested cards.

Key Takeaways

1,L40S-class throughput at 165W single-slot power: At 512-token input/output, the RTX PRO 4500 matched or beat L40S on all FP8/BF16 models tested. On Ministral 3 14B FP8: 1,107 vs 995 tokens/s; Ministral 3 3B: 2,006 vs 1,988 tokens/s. The RTX PRO 4500 uses only 47% of L40S power and occupies half the physical slots.

2,~3× faster than the L4 it replaces: Short-context throughput is 2.8–3.6× the L4, at 2.3× the L4’s board power.

3,32GB memory creates a hard ceiling: At 8K input, RTX PRO 4500 lags L40S by 17–33%. Its throughput plateaus at concurrency 8 while L40S continues scaling to concurrency 16, caused by exhausted KV cache.

4,NVFP4 performance depends on software across all GPUs: On Qwen3.8-27B NVFP4 at concurrency 32: RTX PRO 4500 hit 320 tokens/s, L40S hit 480 (no native FP4 hardware), RTX PRO 6000 hit 621. In this vLLM build, NVFP4 throughput does not scale with memory bandwidth, though MAMF testing shows the RTX PRO 4500’s FP4 hardware reaches 568.6 TFLOPS versus 280.1 TFLOPS in FP8.

5,Higher-tier GPUs mainly gain memory: When capped to 450W (Dell R770 GPU slot limit), RTX PRO 6000 delivers ~2× RTX PRO 4500 throughput at short context and 2.5–3.2× at 8K. Raising the RTX PRO 6000 to full 600W only adds 1–2% short-context performance and 4–9% long-context performance; most of its advantage over the 4500 comes from extra memory.

NVIDIA RTX PRO 4500 Blackwell Server Edition Specifications

Two GPUs share the RTX PRO 4500 Blackwell name but differ. The Workstation Edition, announced at GTC 2025, is a 200W dual-slot active-cooled card with four DisplayPort outputs and 896GB/s memory bandwidth. The Server Edition reviewed here launched at GTC 2026: a 165W, single-slot, headless passive-cooled board with 800GB/s bandwidth. It drops display outputs and some clock headroom for data center features including MIG, confidential computing, triple NVENC/NVDEC, and vGPU 20 support. Both variants use the same 10,496-core GPU and 32GB ECC GDDR7.

The GPU die packs 45.6 billion transistors on a 378 mm² TSMC 4nm custom chip with 82 4th-gen RT cores (82 SMs, 328 Tensor Cores), belonging to the GB203 family. NVIDIA’s quoted Tensor performance numbers include sparsity; dense computation is half that value. Measured dense FP8 peaks hit 805 TFLOPS and FP16 at 403 TFLOPS.

Design and Build

The RTX PRO 4500 Server Edition is a full-height full-length (FHFL), single-slot card measuring 4.4 in × 10.5 in. This differs from the half-height half-length L4, which drew all power from the PCIe slot and fit into 1U servers and small edge boxes. The RTX PRO 4500 requires a 16-pin power connector and chassis airflow for passive cooling. Most standard 1U servers lack the space and required connector, so the GPU targets 2U platforms or specialized whitebox 1U chassis with FHFL slots. It is not a drop-in replacement for L4 hardware deployed in 1U edge systems.

In stacked deployments, one L40S dual-slot space can host two RTX PRO 4500 cards. AWS G7 instances support up to eight RTX PRO 4500 GPUs per host. The card has no display outputs; graphics workloads over vGPU or rendering run across the network via the vented bracket. Its three 9th-gen NVENC and three 6th-gen NVDEC engines support 4:2:2 H.264/HEVC encode/decode and deliver double the H.264 decode throughput per NVDEC compared to L4.

Positioning

NVIDIA describes the RTX PRO 4500’s core value as combining AI, compute, graphics and video acceleration in a 165W passive single-slot package for deployments constrained by rack power, cooling and density. It sits in the mainstream data center and edge segment as the entry point of the Blackwell server GPU family, below the RTX PRO 6000.

NVIDIA’s benchmark claims versus L4 include up to 10× small-model inference on Nemotron Nano, 4× video summarization on Cosmos Reason 2, 1.9× 4K SPECviewperf 15, and 1.8× streaming density. Against dual-socket EPYC 9654 CPUs, eight RTX PRO 4500 cards deliver up to 50× faster vector database performance and up to 100× faster vision AI inference. Dell notes three 32GB RTX PRO 4500 cards cost roughly the same as one RTX PRO 6000. This GPU is ideal for servers with no GPU or legacy L4 cards; it is not a good match for systems engineered for RTX PRO 6000.

Test Setup

Testing used a Dell PowerEdge R770 with dual Intel Xeon 6787P CPUs (86 cores each), 2TB DDR5-6400 memory and NVIDIA driver 595.71.05. Tests used the NGC vLLM 26.08-py3 container with vLLM 0.27.1 and CUDA 13.4.1 for consistent software stacks. Each GPU was tested individually at its rated power limit. The RTX PRO 6000 ran on a Dell Pro Max Tower T2, tested both at default 600W and a manually verified 450W power cap.

vLLM online serving benchmarks ran at concurrency levels of 1, 2, 4, 8, 16, 32 with two test profiles: 512 input / 512 output tokens (chat/short agent tasks) and 8,192 input / 1,024 output tokens (RAG and document processing). Test models: Ministral 3 3B and 8B (BF16), Ministral 3 14B Instruct (FP8), Qwen3.8-27B (NVFP4). We report output token throughput and total throughput including prefill tokens. This test suite excludes large models requiring >48GB VRAM, MIG partitioning, vGPU, video transcoding, power metering, dual 4500 configurations and higher-tier data center GPUs.

Maximum Achievable Matmul FLOPS (MAMF)

MAMF measures sustained dense matrix multiplication throughput to evaluate raw tensor hardware performance. The RTX PRO 4500 achieved 135.9 TFLOPS BF16, 280.1 TFLOPS FP8, and 568.6 TFLOPS NVFP4, reaching ~67–70% of NVIDIA’s published peak values and matching cuBLAS reference figures. The RTX PRO 6000 scaled similarly, delivering 2.6–2.9× the RTX PRO 4500’s throughput across all precisions at 600W. At 450W cap, its FP8 performance stayed nearly unchanged while BF16 and NVFP4 dropped slightly. L40S and L4 lack FP4 tensor hardware. The RTX PRO 4500’s NVFP4 throughput hits 1.5× L40S’s FP8 peak, demonstrating FP4 hardware gains at the GEMM level, though these gains do not fully translate to the vLLM serving stack used.

vLLM Online Serving: Short Context (512/512)

Short context is where the RTX PRO 4500 excels. At concurrency 32, it matched or outperformed L40S on BF16 and FP8 models. Its throughput is 2.8–3.6× faster than L4. The RTX PRO 6000 at 450W cap delivers roughly double the RTX PRO 4500’s throughput; increasing power to 600W only yields minor extra gains. Total throughput including prefill tokens maintains the same performance ranking.

vLLM Online Serving: Long Context (8K/1K)

At 8K input, KV cache memory limits change results. RTX PRO 4500 throughput plateaus at concurrency 8, while L40S continues scaling to concurrency 16. At concurrency 32, RTX PRO 4500 lags L40S by 17–33%. The RTX PRO 6000’s 96GB memory avoids this bottleneck, delivering 2.5–3.2× RTX PRO 4500 throughput at 450W cap, and 2.7–3.5× at full 600W. The power cap penalty becomes more visible in long-context prefill workloads. For document QA, long-context RAG or agent workflows, VRAM capacity is the dominant limiting factor for the RTX PRO 4500.

NVFP4: Where the Software Sets the Ceiling

Qwen3.8-27B NVFP4 leverages Blackwell’s native FP4 tensor cores. At concurrency 32 short context, RTX PRO 4500 output 320 tokens/s; L40S hit 480 tokens/s via weight dequantization, and RTX PRO 6000 hit ~620 tokens/s. At concurrency 1, all GPUs show low single-stream throughput, not scaling with memory bandwidth. This indicates the vLLM NVFP4 kernel implementation is the bottleneck across all hardware. NVIDIA’s TensorRT-LLM stack shows much higher FP4 throughput on the same GPU, confirming the hardware capability exists; users must validate NVFP4 performance on their own serving software stack. Long-context NVFP4 tests show the familiar KV cache plateauing for RTX PRO 4500 and L40S, while RTX PRO 6000 keeps scaling.

Throughput per Rated Watt

Power draw was not measured directly; efficiency uses rated board power. At short context on Ministral 3 14B FP8, RTX PRO 4500 leads the list with 6.7 output tokens/s per watt. L40S scores 2.8 tokens/s/W, L4 scores 5.1, capped RTX PRO 6000 scores 4.8, and full-power RTX PRO 6000 scores 3.8. The RTX PRO 4500 remains the most efficient GPU in this test group for short context. At long 8K context, RTX PRO 4500 efficiency falls as KV cache limits throughput, and the 450W-capped RTX PRO 6000 matches its efficiency while delivering nearly 3× more throughput per slot.

Conclusion

The RTX PRO 4500 Blackwell Server Edition delivers on NVIDIA’s promise: it brings Blackwell capabilities into servers previously limited to L4-class hardware. For mainstream small and medium chat/reasoning LLMs, it delivers L40S-level throughput at less than half L40S power and triples L4 performance.

Its main limitation is 32GB VRAM. While sufficient for its target model sizes, it restricts concurrency for long-context workloads, where L40S and RTX PRO 6000 pull ahead. NVFP4 hardware shows strong raw GEMM performance, but the vLLM build used in testing does not fully unlock this advantage; software maturity will improve FP4 serving performance over time.

This GPU is an excellent upgrade for 2U servers or FHFL-capable 1U hardware needing inference, vision AI, transcoding or virtual workstation acceleration without infrastructure overhauls. Existing L4 users constrained by 24GB VRAM are strong candidates. Organizations running heavy long-context or multi-tenant workloads requiring 48GB+ VRAM should select the RTX PRO 6000 instead.

NVIDIA clearly separates these product tiers, and the 165W RTX PRO 4500 fills the edge AI performance gap between L4 and RTX PRO 6000. The RTX PRO 4500 Blackwell Server Edition earns the Best Single-Slot GPU ranking on the enterprise GPU leaderboard.

Beijing Qianxing Jietong Technology Co., Ltd.
Sandy Yang/Global Strategy Director
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Email: yangyd@qianxingdata.com
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