TL;DR: While RTX 5090 and 5080 cards remain nearly impossible to find at reasonable prices, several excellent alternatives exist. From the still-capable RTX 4090 to professional cards like the RTX 6000 Ada, here are five GPUs you can actually buy for AI workloads in 2026.
---
The Current Landscape
The GPU market for AI buyers has become bifurcated. Consumer cards (RTX 50-series) face severe shortages and price gouging, while professional and previous-generation cards remain available through normal channels. This creates an unusual situation where the "best" GPU on paper might not be the smartest purchase.
Here are five options that balance performance, availability, and value for AI development.
---
1. RTX 4090 - The Practical King
| Spec | Details |
|---|---|
| VRAM | 24GB GDDR6X |
| Memory Bandwidth | 1,008 GB/s |
| MSRP | $1,599 |
| Current Price | $1,800-2,200 |
| Availability | Constrained but findable |
The RTX 4090 remains the workhorse for local AI development. Despite being "previous gen," it handles most practical AI workloads effectively:
- 7B-13B models: Runs comfortably with room to spare
- 30B models: Manageable with 4-bit quantization
- 70B models: Requires aggressive quantization but functional
- Fine-tuning: LoRA/QLoRA on most open-source models
Why buy now: Prices have stabilized. While there's modest premium over MSRP, it's nowhere near the 100%+ markups on RTX 50-series. Cards like the ASUS TUF RTX 4090 and MSI RTX 4090 Gaming X Slim are available through major retailers.
Best for: Individual developers, researchers, and hobbyists who need serious local AI capability without enterprise budgets.
---
2. RTX 4080 Super - The Value Play
| Spec | Details |
|---|---|
| VRAM | 16GB GDDR6X |
| Memory Bandwidth | 736 GB/s |
| MSRP | $999 |
| Current Price | $1,000-1,200 |
| Availability | Good |
The RTX 4080 Super offers 16GB VRAM at reasonable prices - ironically the same VRAM as the shortage-plagued RTX 5070 Ti but actually purchasable.
- Price premium: Minimal over MSRP
- Stock: Widely available
- Performance: ~80% of RTX 4090 in AI inference
Why buy now: If 16GB is sufficient for your workloads (7B-13B models comfortable, 30B quantized), the 4080 Super delivers excellent value. Why pay $1,039+ for an RTX 5070 Ti when the 4080 Super offers similar VRAM at better availability?
Best for: Developers with moderate VRAM needs who prioritize availability over cutting-edge specs.
---
3. RTX 4070 Ti Super - The Budget Option
| Spec | Details |
|---|---|
| VRAM | 16GB GDDR6X |
| Memory Bandwidth | 672 GB/s |
| MSRP | $799 |
| Current Price | $799-900 |
| Availability | Good |
The RTX 4070 Ti Super hits the sweet spot for budget-conscious AI developers:
- 16GB VRAM: Same as RTX 4080 Super and 5070 Ti
- Near-MSRP pricing: Unlike 50-series cards
- Widely stocked: Available from multiple retailers
Why buy now: For $800, you get the VRAM capacity needed for most local AI work without the shortage premium. The tensor cores handle inference efficiently, and 16GB covers 7B-13B models comfortably.
Best for: Budget-conscious developers, students, and those building their first AI workstation.
---
4. RTX 6000 Ada - The Professional Choice
| Spec | Details |
|---|---|
| VRAM | 48GB GDDR6 ECC |
| Memory Bandwidth | 960 GB/s |
| MSRP | ~$6,800 |
| Current Price | $6,500-7,500 |
| Availability | Good through professional channels |
The RTX 6000 Ada exists in a different market entirely - professional visualization and compute. This means:
- 48GB VRAM: 2x the RTX 4090, 1.5x the RTX 5090
- ECC memory: Error correction for reliability-critical work
- No shortage: Professional cards aren't subject to consumer demand spikes
- Enterprise support: Proper drivers and long-term support
Why buy now: If your work requires more than 24GB VRAM and you're tired of fighting consumer shortages, the RTX 6000 Ada delivers. The previous-generation A6000 is also available at lower price points.
Best for: Professional users, research labs, and anyone needing 48GB+ VRAM for production workloads.
---
5. L40S - The Datacenter Alternative
| Spec | Details |
|---|---|
| VRAM | 48GB GDDR6 |
| Memory Bandwidth | 864 GB/s |
| MSRP | ~$8,000 |
| Current Price | $7,500-9,000 |
| Availability | Good through enterprise channels |
The L40S is a datacenter GPU based on Ada Lovelace architecture, designed for AI inference at scale:
- 48GB GDDR6: Massive VRAM for large models
- Optimized for inference: FP8 tensor cores for efficient AI workloads
- Dual-slot form factor: Fits in standard servers
- Passive cooling option: Available for datacenter deployment
Why buy now: For organizations building inference infrastructure, the L40S offers excellent price-per-GB of VRAM and won't become scarce due to gaming demand. Multiple vendors stock H100 and L40S servers:
Best for: Organizations building dedicated AI inference infrastructure.
---
Comparison Table
| GPU | VRAM | Current Price | Availability | Best Use Case |
|---|---|---|---|---|
| RTX 4090 | 24GB | $1,800-2,200 | Constrained | Local development, fine-tuning |
| RTX 4080 Super | 16GB | $1,000-1,200 | Good | Budget AI, 7B-13B models |
| RTX 4070 Ti Super | 16GB | $799-900 | Good | Entry-level AI workstation |
| RTX 6000 Ada | 48GB | $6,500-7,500 | Good | Professional, large models |
| L40S | 48GB | $7,500-9,000 | Good | Datacenter inference |
---
What About RTX 50-Series?
The RTX 5090 (32GB) and 5080 (16GB) are technically superior but:
- RTX 5090: Selling at $3,500-5,000+ when available
- RTX 5080: $1,200+ vs $999 MSRP
- RTX 5070 Ti: Potentially EOL, $1,039+
Until supply normalizes (expected Q3 2026), the cards above offer better practical value.
---
Pre-Built Alternative
If sourcing individual GPUs feels frustrating, workstation builders like Bizon often have GPU allocations that individuals can't access. A complete workstation may actually be easier to acquire than standalone cards.
---
Cloud Option
Remember that cloud GPU providers offer immediate access without hardware hassles. During shortage periods, cloud can bridge the gap while you wait for supply to normalize.
---
Related:
