TL;DR: Conflicting reports suggest the RTX 5070 Ti may be nearing end-of-life, with NVIDIA allegedly shifting production to RTX 5060 series cards. While ASUS walked back its initial statement, stock remains severely constrained. For AI buyers, this reinforces the case for either jumping to professional cards or settling for available alternatives.
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The Controversy
At CES 2026, Hardware Unboxed reported that ASUS told them the RTX 5070 Ti is no longer being produced - meaning cards currently on shelves are the last batch. The same report suggested RTX 5060 Ti 16GB would follow.
ASUS quickly issued a correction, blaming "incomplete information" and stating their 5070 Ti cards have not reached end-of-life status. But here's the thing: whether or not it's officially EOL, the practical reality is the same - stock is severely limited and prices are inflated.
What's Actually Happening
Several data points paint a concerning picture:
- European distributors: Cannot sell RTX 5070 Ti, 5080, or 5090 due to "current market conditions"
- Order limits: Retailers capped at 5 units per model for RTX 5070 variants
- Pricing: RTX 5070 Ti selling at $1,039 on Amazon vs $749 MSRP (39% markup)
- Production shift: NVIDIA reportedly prioritizing RTX 5060 and 5060 Ti 8GB production
The pattern suggests NVIDIA is reallocating limited GDDR7 and TSMC capacity toward higher-volume, lower-VRAM products where memory constraints are less acute.
Why This Matters for AI Development
The RTX 5070 Ti occupies an interesting middle ground for AI workloads:
| Spec | RTX 5070 Ti | RTX 5090 | RTX 4090 |
|---|---|---|---|
| VRAM | 16GB GDDR7 | 32GB GDDR7 | 24GB GDDR6X |
| MSRP | $749 | $1,999 | $1,599 |
| Actual Price | $1,000+ | $3,500+ | $1,800-2,200 |
| Availability | Severely limited | Nearly impossible | Constrained |
For local LLM inference, 16GB is workable for 7B-13B models but tight for anything larger. The 5070 Ti was positioned as an affordable entry point to the 50-series, but current pricing eliminates that value proposition.
What to Do Instead
Option 1: RTX 4090 (If You Can Find One)
The RTX 4090 remains the practical choice for local AI development:
- 24GB VRAM: Handles most consumer AI workloads
- Actual availability: More likely to find than 50-series cards
- Price premium: 20-40% over original MSRP vs 50-100% for 50-series
Cards like the ASUS TUF RTX 4090 or MSI RTX 4090 Gaming X Slim are available through normal retail channels.
Option 2: RTX 4080 Super
The RTX 4080 Super offers 16GB VRAM at more reasonable prices:
- Same VRAM as 5070 Ti: 16GB for similar model capacity
- Better availability: Previous-gen cards aren't as supply-constrained
- Proven performance: Well-documented AI inference benchmarks
Option 3: Professional Cards
If budget allows, professional cards sidestep the consumer GPU shortage entirely:
- RTX 6000 Ada: 48GB GDDR6 ECC, enterprise-grade reliability
- RTX A6000: 48GB GDDR6, previous-gen but widely available
- L40S: 48GB Ada Lovelace, datacenter-class AI performance
Professional cards cost more upfront but aren't subject to the same supply dynamics affecting consumer GPUs.
Option 4: Pre-built Workstations
Workstation builders often have allocations that individual buyers don't:
- Bizon G3000: Available with RTX 5090 or 4090 configurations
- Bizon ZX4000: Water-cooled multi-GPU with professional card options
Option 5: Cloud
When hardware is scarce, cloud GPU providers offer immediate access:
- No waiting for stock
- Scale up or down as needed
- Pay only for what you use
The Bigger Picture
This situation reflects broader dynamics in the GPU market:
- Memory constraints: GDDR7 production can't keep pace with demand
- Margin optimization: NVIDIA prioritizes higher-margin datacenter products
- Volume strategy: RTX 5060 uses less memory, easier to produce at scale
The memory crisis is expected to persist until late 2027 or early 2028. Planning hardware purchases around this reality is prudent.
Recommendations
- If you need 16GB now: RTX 4080 Super is more available and reasonably priced
- If you can stretch budget: RTX 4090's 24GB provides more headroom
- For serious AI work: Professional cards or pre-built workstations avoid consumer supply issues
- For flexibility: Cloud GPU until supply normalizes
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Related:
- The RTX 5090 Shortage: What AI Hardware Buyers Need to Know
- The AI Memory Crisis: Why Your Next GPU Server Will Cost More
- Browse AI Accelerators and GPUs
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