RunPod
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A40 cloud comparison · May 2026
The 48 GB budget workhorse — NVIDIA A40 at $0.39–$0.99/h. 3 clouds compared. Best for ComfyUI multi-model workflows, budget fine-tuning and VFX.
The NVIDIA A40 48GB is the workhorse of budget-conscious ML teams in 2026 — a workstation-grade GPU with 48 GB GDDR6 and ~149 TFLOPS BF16. It costs a fraction of L40S or H100, but 48 GB VRAM means you can run the same multi-model workflows that once required a data-center GPU.
With only 3 providers (RunPod, CoreWeave, Massed Compute), the A40 market is smaller than L40S — but pricing of $0.39–$0.99/h makes it the sweet spot for ComfyUI workflows, budget fine-tuning experiments, and teams loading multiple 13B models simultaneously. Massed Compute leads on price; CoreWeave on enterprise scale.
48 GB is the magic number for multi-model workflows. At $0.39/h (Massed Compute), you can run ComfyUI with a 13B LLM + SDXL + ControlNet loaded simultaneously — a combination that would OOM on a 24 GB RTX 4090 — at roughly the price of a good GPU laptop per day. RunPod adds flexibility with spot and on-demand options.
| Provider | Starting Price | Top GPUs | Highlights | Rating | CTA |
|---|---|---|---|---|---|
| RunPod Editor's Choice | from $0.20/h | RTX 3090, RTX 4090, A100 80GB ≤80GB |
| ★★★★★ | View pricing |
| Massed Compute | from $0.35/h | RTX A6000, A40, A100 80GB ≤80GB |
| ★★★★☆ | View pricing |
| CoreWeave | from $2.06/h | H100 SXM, A100 SXM, A40 ≤80GB |
| ★★★★☆ | View pricing |
Best value GPU cloud — huge selection, community + secure cloud
Workstation-grade GPUs for AI/ML/VFX — A100 from $1.79/h
Enterprise H100 clusters — Kubernetes-native GPU cloud
Massed Compute at $0.39/h is the cheapest A40 on-demand in 2026. RunPod Community Cloud can occasionally go lower on spot pricing. CoreWeave targets enterprise customers and charges $0.99/h, reflecting its InfiniBand-connected multi-GPU configurations.
A40 wins for multi-model ComfyUI workflows: 48 GB VRAM vs 24 GB on RTX 4090 means you can load significantly more models simultaneously. RTX 4090 has higher raw FP32 throughput per dollar and faster per-image generation when VRAM isn't the bottleneck. For large workflows with multiple ControlNets, LoRAs, and IP-Adapters, A40 is the right choice.
Both are 48 GB GDDR6 cards, but L40S is the newer generation with ~5× the BF16 throughput (~733 vs ~149 TFLOPS). L40S has dedicated hardware video encoders and is designed for inference workloads; A40 is a workstation card without these encoders. L40S is 2–3× more expensive. For pure cost-efficiency on older inference tasks, A40 wins.
Yes — with QLoRA (4-bit quantization). A 34B model with QLoRA fits in ~22 GB VRAM, leaving 26 GB headroom for activations and optimizer states on the 48 GB A40. Full fine-tuning of 34B requires multiple GPUs; for single-GPU QLoRA fine-tuning, A40 at $0.39/h (Massed Compute) is one of the best value options available.
Yes — A40 was designed as a workstation GPU for Omniverse, Blender, and DCC applications. It supports ECC memory (important for long renders) and NVENC/NVDEC for video. CoreWeave specifically positions A40 instances for visual effects and 3D compute. At $0.99/h for enterprise-grade reliability, it competes directly with on-premise A40 workstations.
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