Walmart is clearing RTX 4080 Super inventory at $1,019 — that's $482 off the $1,499 MSRP. For a card that launched less than 18 months ago, that's a significant cut. It also puts the 4080 Super in a strange competitive position: priced above the RX 9070 XT at $449, below the RTX 4090 at $1,600, and competing directly with used 3090 prices for the first time.
The question isn't just "is $1,019 a good price?" It's whether a 16GB card at $1,019 makes sense when you can buy 24GB used or 16GB new for less. Let's work through it.
Quick Summary
- RTX 4080 Super at $1,019 is $482 off MSRP — clearance pricing means limited availability
- For local LLM, a used RTX 3090 ($500) offers more VRAM (24GB) at half the cost
- RX 9070 XT at $449 is the best pure-value 16GB card — but AMD ROCm support is weaker
What the RTX 4080 Super Actually Delivers
The 4080 Super is a strong card. It's not the 4080 with minor tweaks — the Super refresh gave it the full AD102 variant with 10,240 CUDA cores and 16GB GDDR6X at 736 GB/s memory bandwidth. For inference workloads, that bandwidth number matters more than the CUDA core count.
RTX 4080 Super specs:
- VRAM: 16GB GDDR6X
- Memory bandwidth: 736 GB/s
- CUDA cores: 10,240
- TDP: 320W
Compare that to the competition:
Current Price
$1,019
~$1,600
$450–$600
$449
~$699 At $1,019, the 4080 Super is faster than the 4070 Ti Super but costs $320 more for the same VRAM. Against a used 3090, it's twice the cost for 8GB less VRAM. Against the RX 9070 XT, it's $570 more for moderately faster compute and NVIDIA ecosystem.
The VRAM Question: Why 16GB Limits You
For local LLM inference, VRAM is the hard constraint. You can't run a model layer that doesn't fit in VRAM — it either gets offloaded to system RAM (5–10x slower) or you have to use a smaller quantization that fits.
At 16GB, here's what you can and can't run cleanly:
Runs well at 16GB:
- Llama 3.1 8B at Q8 (~9GB)
- Mistral Small 4 14B at Q4 (~10GB)
- Qwen2.5 14B at Q4 (~10GB)
- Gemma 3 12B at Q8 (~14GB) — tight but workable
Needs workarounds at 16GB:
- Qwen2.5 32B — needs Q2 or partial CPU offload
- Llama 3.3 70B — requires multi-GPU or heavy offloading
- Any 30B+ model at Q4 — splits into RAM, takes a performance hit
The RTX 3090's 24GB adds roughly 8GB of working space above the 16GB baseline. That 8GB is the difference between running Mistral Small 4 at Q8 cleanly (22GB) vs having to stay at Q4, and it's the difference between running 30B models comfortably vs fighting offloading.
Comparing the Real Alternatives
Used RTX 3090 — ~$500
The 3090 remains the best VRAM-per-dollar option for local LLM. 24GB GDDR6X, 936 GB/s bandwidth, runs Mistral Small 4 at Q8, handles most 30B models at Q4 without complaint.
The downsides: it runs hot (350W TDP on the Founders Edition), it's used hardware with no warranty, and you're buying a previous-generation card. The performance gap vs. the 4080 Super is noticeable on compute tasks — the 4080 Super is roughly 40% faster in raw throughput.
For inference-focused builds where you run one model at a time, that throughput gap is less relevant than the VRAM gap. The 3090 wins on VRAM economics.
RX 9070 XT — ~$449
The new RDNA 4 flagship at 16GB. This is AMD's best price-efficiency card in years — at $449, you're getting performance that trades blows with the 4070 Ti Super at $699. Infinity Cache architecture helps bridge the memory bandwidth gap.
The problem: ROCm. AMD's GPU compute stack for Linux is functional but not polished. Ollama supports it, llama.cpp has ROCm builds, but you'll hit rough edges that CUDA users don't see. Windows ROCm support is even more limited. If you're on Windows and not willing to run WSL2, the 9070 XT is a frustrating choice for local LLM.
For pure value, the 9070 XT is the best 16GB card in 2026. For local LLM with minimal friction, NVIDIA's ecosystem still wins.
RTX 4070 Ti Super — ~$699
This is the honest competitor to the Walmart 4080 Super deal. Same 16GB VRAM, 672 GB/s bandwidth vs 736 GB/s, 285W vs 320W TDP. The 4080 Super beats it in benchmarks, but not by a margin that justifies a $320 price difference.
If the 4080 Super clearance was at $799 this would be a slam-dunk. At $1,019, the 4070 Ti Super at $699 is the better buy for most people who specifically want a 16GB NVIDIA card.
Who Should Actually Buy This
The Walmart clearance RTX 4080 Super makes sense if you meet a specific profile:
- You want new-in-box — not comfortable buying used hardware, want warranty coverage
- You specifically need NVIDIA — you're on Windows, your workflow is CUDA-dependent, ROCm is not an option
- 16GB is enough for your actual workloads — you're running 7B–14B models primarily, not 30B+
- You want the fastest single-GPU card under $1,100 — the 4080 Super wins that category cleanly
If any of those criteria don't fit, the math doesn't hold. The 3090 wins on VRAM value, the 9070 XT wins on price, and the 4070 Ti Super wins on price-to-performance for NVIDIA users who don't need the top-tier.
The clearance window is real — when Walmart clears GPU stock, it moves in weeks, not months. If this card fits your build, don't wait for a further discount that isn't coming.
FAQ
Is the RTX 4080 Super worth buying for local LLM in 2026? At $1,019 it's a decent deal but not exceptional. For local LLM specifically, the 16GB VRAM is the same as cheaper alternatives. If you need the fastest 16GB card on the market and want new-in-box, the clearance price makes it competitive. Otherwise, a used RTX 3090 at $500 gives you 24GB for less money.
How does the RTX 4080 Super compare to the RTX 3090 for local LLM? The 4080 Super is faster on compute workloads but has 8GB less VRAM (16GB vs 24GB). For LLM inference, VRAM is the more important spec. The 3090's 24GB lets you run 30B+ models at Q4 without splitting across RAM, which the 4080 Super cannot do as cleanly.
Will this Walmart clearance deal last? Clearance pricing moves fast — once units are gone, they're gone. Walmart clearance on electronics typically clears out within 1–3 weeks. If you're considering the RTX 4080 Super specifically, don't wait more than a week to decide.