Neueste Cloud-GPUs veröffentlicht 2025 oder später — June 2026

What “released in 2025” means when you rent

Filtering the comparison above to a release year of 2025 or later narrows the catalog to the newest silicon a cloud provider can put in front of you. In practice that means a small, fast-moving cluster of accelerators: NVIDIA’s Blackwell data-center parts (the B200, and the Blackwell Ultra B300 that followed), NVIDIA’s Blackwell consumer-class GeForce RTX 50-series such as the RTX 5090, and AMD’s CDNA 4 Instinct MI350 line. These are the chips that reached broad cloud availability across 2025, as opposed to the 2022-2024 generation (Hopper H100/H200, Ada Lovelace L40S/RTX 4090, AMD CDNA 3 MI300X/MI325X).

Picking newest-first is a deliberate trade-off. You get the highest raw throughput, the largest per-GPU memory pools, and support for the newest low-precision math formats — but you also pay the new-generation premium, and you compete for capacity that is still partly backordered. The sections below explain what the 2025 cohort actually delivers so you can read the table against your workload instead of just chasing the highest number.

What the 2025 data-center GPUs actually bring

The defining theme of the 2025 generation is more memory, faster memory, and lower-precision compute. The headline data-center part, the Blackwell B200, ships with 192 GB of HBM3e and roughly 8 TB/s of memory bandwidth on a dual-die package — a large step over the prior Hopper generation’s 80-141 GB. The Blackwell Ultra B300 pushes that further to 288 GB of HBM3e. On the AMD side, the CDNA 4-based MI350 series also lands at 288 GB of HBM3e, keeping AMD’s traditional memory-capacity advantage.

Three characteristics matter most when you rent these:

• FP4 and FP6 low-precision math. Blackwell’s 5th-generation Tensor Cores and AMD CDNA 4 both add native 4-bit/6-bit formats on top of the existing FP8/FP16/BF16/INT8 path. For inference this is the single biggest lever — you can serve larger models with fewer GPUs if your stack supports the new formats.
• Much larger per-GPU memory. A 192 GB or 288 GB pool means models that previously needed two, four, or eight cards to hold weights and KV cache can now fit on one, simplifying serving and cutting cross-GPU traffic.
• Faster interconnect. Blackwell uses NVLink 5 (around 1.8 TB/s per GPU bidirectional) and rack-scale NVL72 designs that link 72 GPUs as one coherent domain. If you rent a multi-GPU 2025 instance, check whether it is NVLink/Infinity Fabric-connected or merely PCIe-attached — that difference dominates large-model training and tensor-parallel inference performance.

The flip side is power and thermals. The B200 carries roughly a 1000W TDP, up from 700W on the previous flagship, which is why this hardware concentrates in newer, liquid-cooled or high-density facilities. As a renter you don’t manage cooling, but it explains why availability is uneven across regions and providers.

The consumer-class 2025 option

Not every 2025 release is a data-center monster. The Blackwell-based RTX 5090 is a GeForce card with 32 GB of GDDR7 — far less memory than the Instinct/B-series parts, no HBM, and no NVLink on most rental configurations. It sits at the affordable end of the 2025 cohort and is a strong fit for single-GPU fine-tuning, diffusion-image and video generation, rendering, and smaller-model inference where 32 GB is enough. It is the wrong tool for training or serving very large language models, which need the HBM-class memory pools above.

Which 2025 workloads justify the newest hardware

Use the newest generation when the workload genuinely consumes it:

• Large-model and frontier training — needs the HBM capacity, bandwidth, and NVLink/Infinity Fabric scaling of the B200/B300/MI350 class; this is where the 2025 cohort earns its premium.
• High-throughput LLM inference — the big win is fitting a model (plus KV cache) on fewer GPUs and exploiting FP4/FP8 to raise tokens-per-second per dollar.
• Memory-bound fine-tuning of large checkpoints — a single 192-288 GB GPU can replace a small multi-card box.

Conversely, the 2025 flagships are overkill for small-model inference, classic computer-vision, most rendering, and experimentation where a prior-generation card or the RTX 5090 delivers the same result for far less. Reach for the newest tier when memory capacity, interconnect, or low-precision throughput is the actual bottleneck — not by default.

Rental and availability reality for 2025 silicon

Because this is the freshest hardware, two practical things shape your experience. First, it sits at the top of the cost spectrum — newest-generation accelerators rent at a clear premium over the prior Hopper/Ada/CDNA 3 generation, and the data-center parts (B200, B300, MI350) cost meaningfully more per hour than the consumer RTX 5090. The live numbers move, so read them from the comparison above rather than memorizing a rate.

Second, capacity is scarcer. Demand outran supply through 2025 and much of the order backlog stretched into 2026, so on-demand availability of the top parts can be intermittent and spot/interruptible pools shallow. When you compare 2025 instances, check region availability, whether the GPUs are NVLink-connected, how many you can actually reserve at once, and the billing granularity — these vary far more than on mature, widely-stocked previous-generation hardware.

Frequently asked questions

Which GPUs count as “released in 2025”?

The filter surfaces the newest cloud-available silicon: NVIDIA Blackwell data-center parts (B200 and the Blackwell Ultra B300), the Blackwell GeForce RTX 50-series including the RTX 5090, and AMD’s CDNA 4 Instinct MI350 line. The exact mix in the comparison above depends on which providers have stocked each part.

Is a 2025-generation GPU always worth the higher price?

Only when your workload is limited by memory capacity, memory bandwidth, multi-GPU interconnect, or low-precision throughput. For large-model training and high-volume LLM inference the newest tier can be cheaper per unit of work. For small models, rendering, or experimentation, a prior-generation card or the RTX 5090 usually gives the same outcome for less.

Why is availability of 2025 GPUs sometimes limited?

Demand for Blackwell and MI350 hardware exceeded supply through 2025, with a large order backlog extending into 2026. Cloud rental is often the fastest route to access, but on-demand and spot capacity for the top data-center parts can be intermittent and region-dependent — worth confirming in the comparison above before you commit.

Do I need NVLink on a 2025 multi-GPU instance?

If you train large models or run tensor-parallel inference across several GPUs, yes — NVLink (NVIDIA) or Infinity Fabric (AMD) interconnect is far faster than PCIe and strongly affects scaling. For single-GPU work it is irrelevant. Always check how the multi-GPU instances in the table are actually wired.