NVIDIA's RTX PRO 4500 Blackwell packs 32GB of GDDR7 onto a single-slot, 165W card that AWS now runs as the exclusive GPU behind its EC2 G7 instance family. These RTX PRO 4500 Blackwell specs aren't a footnote to the RTX PRO 6000: NVIDIA sells this same 32GB tier as two distinct products, a Server Edition and a Workstation Edition, with two different memory bandwidth numbers, and most third-party listings quote the Workstation figure for a card that's actually running as the Server Edition in every cloud instance you can rent. Here's the full datasheet, the bandwidth split explained, what fits in 32GB, and where to actually rent one now that it's showing up beyond AWS.
TL;DR: RTX PRO 4500 Blackwell Specs and Price
- Memory: RTX PRO 4500 Blackwell Server Edition ships 32GB GDDR7 ECC at 800 GB/s; the Workstation Edition of the same 32GB tier runs 896 GB/s, per NVIDIA's own two product pages.
- Price: AWS EC2 g7.2xlarge (1x RTX PRO 4500 Server Edition) runs from $2.52/hr on-demand as of 29 Jun 2026; aggregator GPU.ai lists on-demand access from $0.720/hr as of September 2026.
- Alternative: Spheron doesn't stock this exact SKU but rents the same-tier RTX 5090 (32GB GDDR7, Blackwell) on-demand at $0.78/hr as of 15 May 2026.
RTX PRO 4500 Blackwell: Full Datasheet
The RTX PRO 4500 Blackwell is a single 32GB GDDR7 die sold as two products with different clocks, power limits, and cooling. Here's every published number from NVIDIA's own product pages, side by side.
| Specification | Server Edition | Workstation Edition |
|---|---|---|
| Architecture | Blackwell | Blackwell |
| Memory | 32GB GDDR7 ECC | 32GB GDDR7 ECC |
| Memory bandwidth | 800 GB/s | 896 GB/s |
| CUDA Cores | 10,496 | Not published on the Workstation product page |
| 5th-Gen Tensor Cores | 328 | Not published on the Workstation product page |
| 4th-Gen RT Cores | 82 | Not published on the Workstation product page |
| FP4 Tensor (dense) | 1.6 PFLOPS | Not published on the Workstation product page |
| FP8 Tensor (dense) | 811 TFLOPS | Not published on the Workstation product page |
| FP16/BF16 Tensor (dense) | 406 TFLOPS | Not published on the Workstation product page |
| TF32 Tensor (dense) | 203 TFLOPS | Not published on the Workstation product page |
| FP32 | 51 TFLOPS | Not published on the Workstation product page |
| RT Core throughput | 154 TFLOPS | Not published on the Workstation product page |
| TDP | 165W | Up to 200W |
| Form factor | Single-slot, passive | Dual-slot, active cooling |
| Display outputs | None (headless) | 4x DisplayPort 2.1 |
| Encode/decode | Not listed on the Server Edition product page | Not listed on the Workstation product page |
| MIG support | Up to 2 instances at 16GB each | Not listed on the Workstation product page |
| PCIe | Gen 5 x16 | Not listed on the Workstation product page |
Both editions also support confidential computing on the Server Edition side, which matters for multi-tenant cloud deployments running untrusted workloads on shared hardware.
RTX PRO 4500 vs RTX 5090: Same 32GB Tier, Different Market
The RTX 5090 is the closest thing NVIDIA sells at the same VRAM capacity and the same architecture generation, and it's a useful sanity check on what "32GB Blackwell" can mean depending on which card you're actually looking at.
| Spec | RTX PRO 4500 (Server) | RTX 5090 |
|---|---|---|
| VRAM | 32GB GDDR7 ECC | 32GB GDDR7 (no ECC) |
| Bandwidth | 800 GB/s | 1,792 GB/s |
| CUDA Cores | 10,496 | 21,760 |
| TDP | 165W | 575W |
| Form factor | Single-slot, passive | Dual-slot/triple-slot, active |
| MIG support | Yes, up to 2x 16GB | No |
The RTX 5090 has roughly double the CUDA cores and more than double the memory bandwidth of the RTX PRO 4500 Server Edition, at more than three times the power draw. That's not a fluke of binning, it's the entire design brief: the RTX PRO 4500 is built to fit a power and thermal envelope that lets a rack of them run dense, unattended inference, while the RTX 5090 chases the highest raw throughput a single 32GB card can produce. For a full breakdown of what the RTX 5090's specs mean for inference workloads, see the RTX 5090 datasheet.
Workstation Edition vs Server Edition: 896 GB/s vs 800 GB/s
The gap between 896 GB/s and 800 GB/s traces to GDDR7 clock speed, not a different memory bus. The Server Edition runs GDDR7 at 25 Gbps for 800 GB/s of bandwidth; the Workstation Edition runs the same 256-bit bus at 28 Gbps for 896 GB/s, according to GPUpoet's breakdown of the Server Edition. Same die, same bus width, different memory clock and a different power and cooling budget to support it.
This distinction is easy to miss and it matters for anyone actually renting the card. AWS EC2 G7, the only major hyperscaler instance family carrying this GPU as of its June 2026 launch, runs the Server Edition exclusively at 800 GB/s. The 896 GB/s figure belongs to the desktop tower card with active dual-slot cooling and DisplayPort outputs, the one you'd buy for a local workstation, not the one behind any cloud GPU instance. Several third-party spec aggregators quote 896 GB/s for the Server Edition anyway, which overstates its real memory-bound decode throughput by 12%.
The practical consequence: if you're modeling inference throughput on a rented RTX PRO 4500, whether on AWS G7 or elsewhere, use the Server Edition's 800 GB/s, not the higher Workstation figure. Decode-phase LLM inference is bandwidth-bound, so that 12% gap shows up directly in tokens per second at a fixed batch size.
What Fits in 32GB: Model Sizing at FP8 and INT4
32GB of ECC GDDR7 covers a specific band of production LLM sizes, roughly the same envelope as the RTX 5090 with the added benefit of ECC memory for production reliability.
| Model | Precision | VRAM required | Fits in 32GB? |
|---|---|---|---|
| Llama 3.1 8B | FP16 | ~16GB | Yes, comfortably |
| Llama 3.1 8B | FP8 | ~8GB | Yes, high headroom for KV cache |
| Mistral 22B | FP8 | ~22GB | Yes, tight on KV cache |
| Qwen2.5 14B | FP16 | ~28GB | Tight, limit context length |
| 30B MoE / dense | AWQ INT4 | ~18-22GB | Yes |
| Llama 3.1 70B | Any usable precision | 70GB+ | No |
| Qwen2.5 32B | FP16 | ~64GB | No |
The ceiling is firm: anything that needs 70B-class weights at FP8 or FP16 does not fit on a single RTX PRO 4500 regardless of edition, and neither edition has NVLink to bridge multiple cards for tensor parallelism. Multi-GPU RTX PRO 4500 deployments scale by running independent model replicas across cards, not by splitting one large model across them. For a broader model-to-GPU sizing reference across VRAM tiers, see Best NVIDIA GPUs for LLMs in 2026.
Where the RTX PRO 4500 earns its keep over a consumer card at the same 32GB capacity is ECC memory and up to two MIG instances at 16GB each. That MIG split lets a single card run two independent 8B-class inference workloads with hardware-level isolation, useful for multi-tenant serving where you don't want one job's memory pressure to affect another's, something the RTX 5090 cannot do at all.
RTX PRO 4500 vs L4 and L40S on Inference Throughput
The RTX PRO 4500 sits between two Ada Lovelace-generation cards that Spheron and most cloud providers already stock, and the comparison against each tells a different story.
Against the L4 (its AWS G6 predecessor): the RTX PRO 4500's 10,496 CUDA cores are roughly 41% more than the L4's 7,424, according to Exxact's breakdown of the Server Edition. TDP more than doubles too, from the L4's 72W to the RTX PRO 4500's 165W, in the same single-slot passive form factor class. That extra power budget buys a real generational jump: 32GB GDDR7 versus the L4's 24GB GDDR6, and native FP4 support the L4's Ada Lovelace Tensor Cores don't have at all.
Against the L40S: this is the comparison most spec sheets get wrong. NVIDIA's L40S runs 48GB of GDDR6 ECC at 864 GB/s, on the AD102 die, drawing 350W with no NVLink, per NVIDIA's own L40S product page. At 864 GB/s, the L40S actually beats the RTX PRO 4500 Server Edition's 800 GB/s bandwidth, despite the RTX PRO 4500 running a newer Blackwell die. It only falls behind the RTX PRO 4500 Workstation Edition's 896 GB/s. If you take the commonly misquoted 896 GB/s figure at face value for the Server Edition, you'd wrongly conclude the RTX PRO 4500 out-bandwidths the L40S in every case; it doesn't, not in the form you can actually rent.
Where the RTX PRO 4500 pulls ahead of the L40S is architecture generation: FP4 Tensor Core support the L40S's Ada Lovelace silicon lacks, and less than half the power draw (165W vs 350W) for models that fit in 32GB rather than needing the L40S's extra 16GB. Where the L40S wins outright is capacity. 48GB fits models the RTX PRO 4500 simply cannot run, like 30B at FP16 or 70B at aggressive quantization with real batch headroom. Our L40S inference benchmark guide has the throughput numbers for what that extra headroom actually buys at scale, and the L4 vs L40S cost breakdown covers the Ada-generation predecessor lineage in full.
RTX PRO 4500 vs RTX PRO 6000 Blackwell: When 32GB Isn't Enough
The RTX PRO 6000 Blackwell is the card to reach for once 32GB stops being enough, and the gap between the two is bigger than a simple capacity bump.
That extra headroom changes what fits on one card. The RTX PRO 4500's 32GB tops out around 30B models at INT4/AWQ quantization; the RTX PRO 6000's 96GB fits 70B models at FP8 with roughly 26GB left over for KV cache, and 30B AWQ models with so much headroom that a single card matched a 4x RTX 4090 setup at roughly 8,900 tokens per second in CloudRift's published benchmark. Both cards share the same Blackwell FP4 and FP8 Tensor Core support and both skip NVLink entirely, so neither is built for splitting a single oversized model across multiple GPUs.
The decision comes down to your model ceiling, not raw preference. If your roadmap stays under 32B parameters, quantized or not, the RTX PRO 4500's lower power draw and single-slot density make it the more efficient fit per rack unit. If you need 70B on one card without falling back to multi-GPU tensor parallelism, the RTX PRO 6000's 96GB is the only single-card option that gets you there. For the die-level detail on how Blackwell's GB202 silicon and FP4 Tensor Cores behave across this product family, see the RTX 5090 vs RTX PRO 6000 Blackwell comparison, and for where the RTX PRO 5000 sits between the two on the same die family, see RTX PRO 5000 vs RTX PRO 6000 Blackwell: cheapest to rent.
RTX PRO 4500 Blackwell Server Edition Price: Where to Rent It Beyond AWS G7
AWS EC2 G7 was the RTX PRO 4500's launch vehicle and, for months, the only place to rent it. The smallest single-GPU instance, g7.2xlarge, runs from $2.52/hr on-demand as of 29 Jun 2026, scaling up to the 8-GPU g7.48xlarge. Our AWS EC2 G7 pricing breakdown covers every instance size, spot discounts, and the hidden egress and Savings Plan costs that sit on top of the sticker price.
That exclusivity is loosening. GPU.ai, a cloud GPU pricing aggregator, now lists RTX PRO 4500 on-demand availability from $0.720/hr as of September 2026, well below AWS's list price for the same card, reflecting broader marketplace availability outside the hyperscaler channel.
NVIDIA describes the Server Edition as built "to accelerate AI inference, data science, and visual computing. With a power-efficient, 165 W single-slot form factor, the GPU provides flexible capabilities and powerful acceleration for data center, edge, and cloud deployments," per Exxact's product summary.
Spheron does not currently stock the RTX PRO 4500 as a specific SKU. If you specifically need this card, to mirror an AWS G7 deployment exactly or to use its ECC-certified data center driver stack, AWS or a marketplace aggregator like GPU.ai is where you'd rent it. What Spheron does carry is the same 32GB Blackwell tier on the RTX 5090, plus a path up to 48GB on the L40S and 96GB on the RTX PRO 6000, all with live rates aggregated across 5+ providers, per-minute billing, no minimum commitment, and no data egress fees, unlike AWS's $0.09/GB.
| Configuration | Type | Price |
|---|---|---|
| RTX 5090 (1x GPU, 32GB GDDR7) | On-demand | $0.78/hr |
| RTX 5090 (1x GPU, 32GB GDDR7) | Spot | $0.89/hr |
| L40S (1x GPU, 48GB GDDR6 ECC) | On-demand | $0.96/hr |
| RTX PRO 6000 (1x GPU, 96GB GDDR7 ECC) | On-demand | $2.35/hr |
Pricing fluctuates based on GPU availability. Spheron rates above are live as of 15 May 2026; AWS and GPU.ai figures reflect their most recently published rates and may have changed. Check current GPU pricing → for live rates.
For 32GB Blackwell inference without an AWS-specific requirement, the RTX 5090 rates above cover the same tier. For workloads that need more headroom, L40S GPU pricing covers the 48GB step up, and RTX PRO 6000 pricing covers the 96GB option. Deployment setup, SSH access, and instance configuration are covered in the Spheron docs.
The RTX PRO 4500 isn't on Spheron's menu yet, but the 32GB Blackwell tier it competes in is, on RTX 5090, with no egress fees and per-minute billing instead of AWS's hourly increments.
Frequently Asked Questions
AWS EC2 g7.2xlarge, the smallest instance carrying one RTX PRO 4500 Blackwell Server Edition GPU, runs from $2.52/hr on-demand as of 29 Jun 2026. GPU.ai, which aggregates rates across multiple cloud providers, lists on-demand access from $0.720/hr as of September 2026. For contrast, the larger RTX PRO 6000 Blackwell with 96GB sits well above both on a per-GPU basis on most marketplaces, since it is a different, more expensive card rather than a cheaper way to get to the same 32GB tier.
Not on raw throughput. Both are 32GB GDDR7 Blackwell cards, but the RTX 5090 has roughly double the CUDA cores (21,760 vs 10,496), roughly double the memory bandwidth (1,792 GB/s vs the RTX PRO 4500 Server Edition's 800 GB/s), and a 575W TDP against the RTX PRO 4500's 165-200W. The RTX PRO 4500 wins on power efficiency, single-slot passive cooling for dense rack deployment, ECC memory, and MIG support, none of which the consumer RTX 5090 offers. Pick the RTX 5090 for raw inference throughput per card; pick the RTX PRO 4500 for power-constrained, ECC-certified, high-density deployments.
Both carry 32GB of GDDR7 ECC on the same 256-bit bus, but they run the memory at different clock speeds. The Server Edition uses 25 Gbps GDDR7 for 800 GB/s of bandwidth, single-slot passive cooling, and a 165W TDP, built for rack-mounted density. The Workstation Edition uses 28 Gbps GDDR7 for 896 GB/s, dual-slot active cooling, and up to 200W, built for a desktop tower with display outputs. Cloud instances, including AWS EC2 G7, run the Server Edition at 800 GB/s, not the 896 GB/s Workstation figure that gets quoted for the card generally.
32GB on the RTX PRO 4500 covers 8B models at FP16, 14B models at FP16 with tight context, and 30B-32B models quantized to INT4/AWQ. It does not fit 70B models at any usable precision. The RTX PRO 6000 Blackwell's 96GB fits 70B at FP8 with room for KV cache and 30B AWQ with vast headroom for high concurrency, at more than double the memory bandwidth (1.792 TB/s vs the RTX PRO 4500's 800-896 GB/s). If your model roadmap stays under 32B, the RTX PRO 4500 tier is the cheaper fit; if you need 70B on one GPU, size up to the RTX PRO 6000.
No, Spheron does not currently stock the RTX PRO 4500 Blackwell as a specific SKU. The closest match by VRAM and generation is the RTX 5090 (32GB GDDR7, Blackwell), available on-demand and spot with per-minute billing and no egress fees. Spheron also lists the L40S (48GB GDDR6 ECC) and RTX PRO 6000 (96GB GDDR7 ECC) for workloads that outgrow 32GB. A reader who specifically needs the RTX PRO 4500 SKU itself, to match an AWS G7 deployment or for its ECC-certified data center driver stack, has to rent it from AWS or a marketplace aggregator instead.
