GPU Market February 2026: RTX 50 Deals Exist but Median Buyer Still Pays 75-90% Over MSRP

RTX 50 Series: Deals Exist, but Patience Required

A year after launch, the RTX 50 series market has a split personality. The chart below shows the best available deals (lowest average of 3 cheapest listings) — and those deals are near or below MSRP. But the typical listing tells a different story:

The gap here is striking. You can find an RTX 5060 for $253 — 15% below MSRP. But the median buyer paid $521, a 74% premium. The pattern is consistent across the whole lineup: best deals are near MSRP, median prices are roughly double that.

Why such a big gap? Those near-MSRP listings are fleeting. I checked the data: the cheapest RTX 5090 listings in January were an ASUS ROG Astral at $1,989 and an FE at $1,996 — essentially MSRP. Each appeared in our data exactly once before selling. Out of 1,489 total RTX 5090 listings in January, only a handful were anywhere near MSRP. The rest? $3,000+. The “best deal” column reflects real prices that real sellers listed at — but you had to be watching at the right moment to grab them.

The Used Market Split: Budget GPUs Rise, High-End Falls

The used GPU market is doing two things at once. Budget and entry-level cards are rising as buyers priced out of new RTX 50 stock turn to last-gen alternatives. But high-end last-gen cards are falling as RTX 50 series availability improves:

My read on this: the split makes sense. Budget GPUs (RTX 3060, 3080, 4060) are rising because they serve buyers who can't justify RTX 50 pricing. High-end last-gen cards (RTX 4070 Ti, 4070 Super, RX 6800 XT) are falling because RTX 50 cards are now available near MSRP, making those last-gen flagships less compelling. The RTX 3070's 63% decline is an outlier — I believe that reflects abnormally inflated December pricing correcting, not a genuine value crash.

Prices shown are overall averages across all active eBay listings for each GPU. Month-over-month comparisons use December 2025 vs January 2026 averages.

Memory Shortage: What GPU Poet's Data Actually Shows

There's been widespread concern that rising DRAM and NAND prices will push GPU prices higher in 2026. GDDR7 supply is tight, GDDR6 pricing has reportedly increased, and HBM (used in data center GPUs) remains allocated months in advance. Last month I said I didn't have a strong opinion on this. This month I dug into our pricing data to see if there's actual evidence one way or the other.

Evidence the shortage is affecting prices

My take

The data actually supports the memory shortage narrative more than I expected. Data center GPUs using HBM are surging (+23-29%), RTX 50 series cards using GDDR7 have median prices 75-90% above MSRP, and budget used cards using GDDR6/6X are rising (+8-12%). High-end last-gen cards are the one exception, falling 13-22% — likely because RTX 50 availability (even at premium prices) is pulling high-end buyers away from the used RTX 40 market.

The budget card increases (+8-12%) are more consistent with demand displacement — buyers priced out of new cards bidding up cheap used alternatives — than with component cost pressure. The high-end last-gen cards falling 13-22% undermines the memory shortage narrative for consumer GPUs specifically.

So where do I land? I think the memory shortage is real for data center / HBM products, but its impact on consumer GPU pricing is overstated. The primary driver of consumer price movements right now is demand shifts, not supply constraints. If you're buying a consumer GPU, don't let memory shortage fears rush your decision. If you're buying data center hardware, prices are moving against you quickly.

Best GPU for Counter-Strike 2: Dollar-Per-Frame Rankings

I wanted to answer a simple question: if you play CS2 competitively, which GPU gives you the most frames for the fewest dollars? I combined CS2 benchmark data at 1440p with current lowest used eBay prices to calculate a dollar-per-frame cost for each GPU. Lower $/FPS is better:

FPS data from Phoronix Test Suite CS2 benchmarks at 2560x1440. RTX 3070 FPS estimated from 3070 Ti results. Used prices are lowest average eBay prices (average of 3 cheapest listings).

The results are striking. The RTX 3070 at $145 used comes in at $0.81 per frame — under a dollar for each frame of CS2 at 1440p. It delivers ~180 FPS, well above the 144 FPS target for competitive play. To put that in perspective: the RTX 4090 costs 6.9x more per frame and only delivers 2.1x more FPS. For pure cost efficiency, used last-gen cards dominate this ranking.

Best Used Deals: Gaming GPUs Below MSRP

With RTX 50 series now widely available, older GPUs continue trading well below their original MSRP. These are the deepest discounts:

The discounts here are massive — 70% or more off original MSRP for all five GPUs. The RTX 3070 at $145 and the RTX 3080 Ti at $363 stand out as real value for 1440p gaming. These prices reflect the lowest average of 3 cheapest listings, so they're realistic prices you can actually buy at.

AMD Alternatives Worth Considering

AMD's last-gen Radeon cards continue to offer value, especially for buyers who don't need ray tracing or CUDA:

The RX 6950 XT at $335 (-70% off MSRP) trades blows with an RTX 3080 Ti in rasterization workloads. The RX 6900 XT at $290 (-71%) is also a strong option. These are lowest average prices from the 3 cheapest listings, making them realistic purchase targets.

Best GPU for AI Inference on a Budget

If you're running models locally — whether for privacy, cost savings, or experimentation — inference needs enough VRAM to hold the model and decent INT8/FP16 throughput. Power efficiency matters for always-on deployments.

I keep coming back to the Tesla P100 at $83 — 16GB of HBM2 for $5 per gigabyte. It lacks Tensor Cores, so it won't win any speed benchmarks, but for experimenting with quantized 7B models it's hard to argue with the price.

Prices are lowest average of 3 cheapest eBay listings.

Best GPU for AI Training on a Budget

Training requires maximum VRAM (to fit model + gradients + optimizer states) and strong FP16/FP32 throughput. Consumer GPUs with 24GB+ are surprisingly competitive here.

The RTX 3090 at $599 is remarkable value — 24GB of VRAM with consumer-grade driver support and a large ecosystem of tutorials and tools. It can fine-tune 7B parameter models with LoRA and run 13B models for inference comfortably. The V100 32GB at $703 beats it on $/GB and has ECC memory for reliable training runs.

Prices are lowest average of 3 cheapest eBay listings.

AI GPU Market: Data Center Prices Surge

This was the most striking finding in this month's data. Data center and AI-focused GPUs saw the largest month-over-month price increases of any category:

Prices are average active eBay listings across all conditions.

I think what's happening here is a combination of continued AI infrastructure build-out and increasing demand from hobbyists and startups, partly driven by open-source model releases (DeepSeek, Llama variants) that make it practical to self-host. The H100 and A100 surges (+29% and +23%) are the standouts — these are the workhorses of commercial AI inference and training. The T4's 18% increase is notable because it's a 2018 inference card, suggesting demand is broad, not just concentrated at the high end. The L40 and L40s saw modest gains, possibly because their higher base prices limit the buyer pool.

Month-Over-Month Price Changes

Here are the most significant price drops this month. The chart shows the 5 biggest movers — all declines:

The RTX 3070's 64% drop dominates the chart. I believe this is a correction from abnormally inflated December pricing rather than a new trend. Outside of that outlier, the theme is high-end last-gen cards continuing to lose value as RTX 50 supply improves.

6-Month Price Trends

This month I'm tracking three GPUs across different market tiers: the RTX 5080 (new generation), the RTX 4070 Super (current generation), and the RTX 3080 (used last-gen):

Buy / Wait / Sell Recommendations by Use Case

For Gaming

For AI / Machine Learning

Methodology

This report uses real-time eBay listing data tracked by GPU Poet. I analyze 90,000+ historical listings across 72 GPU models to identify pricing trends and value opportunities. Gaming benchmark data is sourced from the Phoronix Test Suite / OpenBenchmarking.org community benchmarks. Kudos to Michael Larabel and the Phoronix community for maintaining that resource.

All prices are from US eBay listings in January 2026. “Lowest average” prices (used in charts, CS2 table, and AI tables) represent the average of the 3 cheapest listings for each GPU, providing a realistic “best price you can actually get” figure. Month-over-month comparisons in the price changes section use overall averages across all listings. MSRP figures are official launch prices from NVIDIA, AMD, and Intel.