Best GPU for Stable Diffusion in 2026
Updated August 14, 2026. All prices are launch MSRPs from our GPU database; we do not track street prices.
How fast a card generates images depends on its memory bandwidth, and the benchmarks below make that visible.
For Stable Diffusion and SDXL image generation in 2026, the NVIDIA GeForce RTX 5090 is the best GPU overall because its 32 GB of GDDR7 and 1,792 GB/s of bandwidth produce the highest measured generation throughput of any consumer card. The best budget pick is the GeForce RTX 4060 Ti 16GB at a $499 MSRP, and the best value on the used market is the RTX 3090 with 24 GB. This guide ranks the options using benchmark data from our June 2025 database records.
How fast is each GPU at image generation?
The table below compares SDXL Turbo generation speed in ComfyUI with the specification data behind each card. Images per minute were recorded in June 2025; the RX 7900 XTX result was measured on ROCm.
| GPU | VRAM | Bandwidth | TDP | MSRP | SDXL Turbo (img/min) | Price check |
|---|---|---|---|---|---|---|
| GeForce RTX 5090 | 32 GB | 1,792 GB/s | 575 W | $1,999 | 120 | Check Price |
| GeForce RTX 4090 | 24 GB | 1,008 GB/s | 450 W | $1,599 | 80 | Check Price |
| GeForce RTX 5080 | 16 GB | 960 GB/s | 360 W | $999 | 65 | Check Price |
| GeForce RTX 4080 SUPER | 16 GB | 736 GB/s | 320 W | $999 | 58 | Check Price |
| GeForce RTX 3090 | 24 GB | 936 GB/s | 350 W | $1,499 | 45 | Check Price |
| GeForce RTX 4060 Ti 16GB | 16 GB | 288 GB/s | 160 W | $499 | 28 | Check Price |
| Radeon RX 7900 XTX | 24 GB | 960 GB/s | 355 W | $999 | 40 | Check Price |
Benchmark attribution: Tom's Hardware measured the RTX 5090, RTX 4090, and RX 7900 XTX; TechPowerUp measured the RTX 5080, RTX 4080 SUPER, and RTX 4060 Ti 16GB; Puget Systems measured the RTX 3090. Diffusion throughput tracks memory bandwidth closely, which is why the ranking follows the bandwidth column.
Which GPU is best for high-volume image generation?
Best overall: GeForce RTX 5090. According to Tom's Hardware, it generates SDXL Turbo images at 120 images per minute in ComfyUI, the highest figure in our benchmark database.
The specification profile explains the result: 32 GB of GDDR7 on a 512-bit bus delivers 1,792 GB/s of bandwidth, and 21,760 CUDA cores provide the compute behind each denoising step. The 32 GB pool also matters for workload headroom, because batch generation and additional models such as ControlNet all consume VRAM on top of the base checkpoint. The costs are a $1,999 MSRP and a 575 W TDP that requires a well-cooled system. Buyers who generate professionally will notice the throughput difference daily; casual users will not.
Which GPU is best for Stable Diffusion on a budget?
Best budget pick: GeForce RTX 4060 Ti 16GB. It is the cheapest new NVIDIA card in our database with 16 GB of VRAM, at a $499 MSRP with a modest 160 W TDP.
According to TechPowerUp, the RTX 4060 Ti 16GB generates SDXL Turbo images at 28 images per minute, which is the slowest new-card figure in the table. The case for it is capacity, not speed: 16 GB of VRAM covers SDXL and SD3.5-class checkpoints with room for batching, and the card runs in ordinary desktops without power or cooling upgrades. Buyers whose alternative is a 12 GB card will feel the extra memory long before they miss the speed.
Which used GPUs are worth buying for diffusion?
Best used value: GeForce RTX 3090. It matches the RTX 4090's 24 GB of VRAM at a much lower used-market price, and Puget Systems measured it at 45 SDXL Turbo images per minute.
The RTX 4090 is the stronger used buy when budget allows: Tom's Hardware measured 80 images per minute from its 1,008 GB/s of bandwidth, the highest figure among 24 GB cards in our table. Between them sits the RTX 4080 SUPER at $999 MSRP with 58 images per minute per TechPowerUp, and the RTX 5080 at the same launch price with 65 images per minute on its 960 GB/s of GDDR7. All four cards appear in the price-check column of the table above, so current retail listings are one click away.
How much VRAM does Stable Diffusion need?
Most Stable Diffusion workflows run on 16 GB cards, while the largest diffusion checkpoints benefit from 24 GB or more. Capacity buys workflow freedom rather than raw speed.
The evidence in our database is benchmark-based rather than formula-based. Every 16 GB card in the table generates SDXL Turbo images at full throughput, and TechPowerUp's estimate for the 12 GB Arc B580 comes in at 18 images per minute, so even 12 GB handles SDXL-class models. The 24 GB tier earns its keep with larger checkpoints and heavier batch workflows: the RX 7900 XTX's 40 images per minute on ROCm and the RTX 3090's 45 both leave VRAM to spare. Cards in the 12 GB class, such as the RTX 3060 that anchored budget builds for years, remain usable for SDXL but leave little headroom for batching.
Buyers targeting the largest open image models should also read our dedicated Flux.1 GPU guide, because that workload shifts the VRAM target upward.
Can AMD or Intel GPUs run Stable Diffusion?
Yes, with software caveats. The Radeon RX 7900 XTX runs SDXL Turbo at 40 images per minute per Tom's Hardware ROCm testing, while Intel's Arc B580 manages an estimated 18 images per minute per TechPowerUp.
The specification comparison favors AMD on paper at the same $999 MSRP as the RTX 4080 SUPER: 24 GB of VRAM against 16 GB, and 960 GB/s against 736 GB/s. The measured throughput gap in our table, 40 against 58 images per minute, reflects the CUDA-first software stack that most diffusion tools assume. AMD requires the ROCm stack or Vulkan paths, which work but add configuration. Buyers who mainly generate images and enjoy tweaking software get fair value from AMD; buyers who want every ComfyUI extension to install cleanly should stay on NVIDIA.
Which 16 GB GPU gives the most diffusion speed?
The GeForce RTX 5080 is the fastest 16 GB card for diffusion in our database. TechPowerUp measured 65 SDXL Turbo images per minute from its 960 GB/s of GDDR7, ahead of the RTX 4080 SUPER's 58.
The alternative view favors the used RTX 3090: for buyers who can find one, its 24 GB of VRAM costs less than a new 5080 while trading away speed, at 45 images per minute per Puget Systems. That is the recurring trade in image generation hardware — bandwidth buys images per minute, capacity buys workflow size, and mid-range buyers choose which matters more.
What about the RTX 4070 Super and RTX 4070 Ti Super?
Both cards remain common in stores and sit between the budget and high-end tiers in NVIDIA's lineup. They are workable diffusion cards, but our benchmark database holds no measured generation figures for them, so we do not rank them numerically.
What we can say from the surrounding tiers: the RTX 4070 Ti Super carries the same 16 GB memory class as the cards above and slots below them on price, while the RTX 4070 Super targets the 12 GB class alongside cards like the RTX 3060 that long anchored budget builds. If a discounted listing beats our ranked picks' street prices, the VRAM class table above tells you which tier of workflow it supports.
What are the pros and cons of the top picks?
Each recommendation gives something up. This is the summary buyers most often need.
- RTX 5090: 120 img/min and 32 GB of VRAM; $1,999 MSRP and 575 W of heat to manage.
- RTX 4090 (used): 80 img/min with 24 GB; previous-generation card, no warranty when bought used.
- RTX 5080: fastest 16 GB card at 65 img/min; 16 GB ceiling for the largest checkpoints.
- RTX 4060 Ti 16GB: cheapest new 16 GB card at $499; 28 img/min is the slowest new-card figure we track.
- Used RTX 3090: 24 GB of capacity at used-market pricing; 45 img/min and a 350 W draw from 2020 silicon.
Notice that no pick is strong on every axis: capacity, throughput, price, and power draw trade off in every row.
Who should NOT buy a high-end diffusion GPU?
Buyers generating a handful of images per week should not buy any card in the top half of the table. The RTX 4060 Ti 16GB at $499 already produces 28 images per minute, which outpaces casual usage by a wide margin.
Buyers who need large batches only occasionally should compare against cloud rental too: our cloud pricing database lists single RTX 4090 instances at $0.34 per hour on RunPod, enough for burst generation without owning the hardware. High-end diffusion GPUs pay off when generation runs daily or latency between iterations matters to paid work.
How did we rank these GPUs?
We ranked the cards on measured SDXL Turbo throughput in ComfyUI from our benchmark database, recorded in June 2025 from Tom's Hardware, TechPowerUp, and Puget Systems, with each figure labeled by source and estimate status. Specification values come from manufacturer datasheets in our GPU database.
We report launch MSRPs only, never street prices, because listings move constantly. Rankings weigh generation throughput first, then VRAM capacity, then power draw and price. Cards without measured database entries, such as the RTX 4070 Super tier, are discussed qualitatively rather than ranked. Affiliate relationships do not influence rankings.
Frequently Asked Questions
What GPU do I need for SDXL?
A 16 GB card covers SDXL workflows with batching headroom, and even 12 GB cards run SDXL-class models per our Arc B580 estimate of 18 images per minute. The 24 GB tier matters mainly for larger checkpoints and heavy batch queues.
Is the RTX 3090 still good for image generation?
Yes. Puget Systems measured 45 SDXL Turbo images per minute, and its 24 GB of VRAM handles the same checkpoint classes as the RTX 4090. The trade-offs are speed and the risks of used hardware.
How much faster is the RTX 5090 for image generation?
According to Tom's Hardware, the RTX 5090 generates 120 SDXL Turbo images per minute against the RTX 4090's 80 and the RTX 4060 Ti 16GB's 28. The advantage comes from 1,792 GB/s of GDDR7 bandwidth plus 21,760 CUDA cores.
Can AMD GPUs run Stable Diffusion well?
The RX 7900 XTX reaches 40 images per minute on ROCm per Tom's Hardware, with 24 GB of VRAM at a $999 MSRP. It is viable, but the CUDA-first tooling around ComfyUI makes NVIDIA the lower-friction choice.
Which GPU under $1,000 is best for diffusion?
The RTX 5080 at its $999 MSRP, with 65 images per minute per TechPowerUp and 16 GB of GDDR7. A used RTX 3090 is the capacity-first alternative at the same budget.
Sources
Specifications are manufacturer datasheet values from our GPU database; benchmark figures are from the named third-party sources below.
- Tom's Hardware GPU Benchmarks 2025 — https://www.tomshardware.com/pc-components/gpus
- TechPowerUp GPU Reviews — https://www.techpowerup.com/reviews/
- Puget Systems Hardware Testing — https://www.pugetsystems.com/labs/
- NVIDIA Official Specifications — https://www.nvidia.com/en-us/data-center/
Related reading: our Flux.1 GPU guide, the local LLM GPU guide, and the best GPU under $500 roundup. Head-to-head comparisons: RTX 5090 vs RTX 5080, RTX 5080 vs RTX 4080 Super, and Arc B580 vs RX 7600 XT for budget builds.
Disclosure: CompareAIHardware.com participates in the Amazon Associates program and earns from qualifying purchases through links on this page. Affiliate relationships do not influence our recommendations.