Blog/RTX 50 Super for AI
Hardware · November 2026

RTX 50 Super and the RTX 5080 24GB: what is known, what is rumored, and what 24 GB would run

By Samuel Seidel · Published November 7, 2026 · Sources checked November 7, 2026

As of 7 November 2026, NVIDIA has announced no RTX 50 Super card. The newest report, from Taiwan's BenchLife via VideoCardz on 2 November 2026, describes a 24 GB RTX 5080 planned for Q1 2027 that would replace the 16 GB model, but says board partners had no design kits by the end of October. The reason for the long delay, per a VideoCardz source in July 2026, is memory: a 3 GB GDDR7 chip cost $60 to $70 against about $20 for a 2 GB chip. By my calculation, a 24 GB card would load a 27B dense model at 4-bit with about 119,000 tokens of FP16 KV cache. A 16 GB card cannot load it at all.

ClaimStatusSourceDate
Any RTX 50 Super announced by NVIDIANoVideoCardz: "NVIDIA has never publicly confirmed" it2026-06-05
RTX 5080 Super: 24 GB GDDR7, 256-bit, 10,752 CUDA cores, 32 Gbps, 415 WRumor (leaks)TweakTown2025-11-10
Rumored US price $999 to $1,199Rumor, set before the shortageTweakTown (same article)2025-11-10
Finished Super cards at a board partner, on holdReported by an unnamed sourceVideoCardz2026-07-17
3 GB GDDR7 chip $60 to $70, 2 GB chip about $20Reported by the same sourceVideoCardz (same article)2026-07-17
24 GB RTX 5080 in Q1 2027, replacing the 16 GB modelRumorBenchLife via VideoCardz2026-10-12
No design kits at partners by end of OctoberRumorBenchLife via VideoCardz2026-11-02
Cheapest RTX 5080 16 GB in GermanyListed price, incl. 19% VATGeizhals: from €1,849.99checked 2026-11-07

Rumors are labeled with the outlet that published them and its original source. Nothing in the "rumor" rows has been confirmed by NVIDIA.

Has NVIDIA announced the RTX 50 Super?

No. NVIDIA has said nothing official about a Super refresh, and the dates in the press have moved four times in a year. Here is the trail, oldest first.

Neither outlet knows whether "RTX 5080 24GB" is the old RTX 5080 Super under a new name. TechSpot's Q4 2026 pricing update repeats the Q1 2027 rumor and adds that retail sources report rising wholesale costs for the current 16 GB card.

Why do 3 GB GDDR7 chips decide the RTX 50 Super?

Because the whole refresh is a memory swap: same GPUs, same buses, denser chips. Each GDDR7 chip sits on a 32-bit channel, so the RTX 5080's 256-bit bus (NVIDIA spec page) carries eight chips. Eight 2 GB chips give 16 GB. Eight 3 GB chips give 24 GB. The 192-bit RTX 5070 goes from 12 GB to 18 GB the same way.

The chips exist. Samsung announced the first 24-gigabit (3 GB) GDDR7 on 17 October 2024, at 40 Gbps, aimed at data centers and AI workstations as well as graphics cards. A 24 GB GB203 also exists already: the RTX 5090 Laptop GPU uses the GB203 chip with 24 GB on a 256-bit bus (Notebookcheck), which by the same arithmetic means eight 3 GB chips. So does a workstation card, the RTX PRO 4000 Blackwell, with 24 GB on a narrower 192-bit bus at 672 GB/s and 140 W (Geizhals spec listing).

What changed is price. Using the chip prices VideoCardz's source gave in July 2026:

16 GB card:  8 chips x $20      = $160 of GDDR7  ($10.0 per GB)
24 GB card:  8 chips x $60-70   = $480-560       ($20.0-23.3 per GB)
extra cost per card                = $320-400 before any margin

That is my arithmetic on reported prices, not a bill of materials. TrendForce's 30 September 2026 forecast says graphics DRAM prices keep rising into Q4 2026 because GDDR6 supply is shrinking and GDDR7 output stays limited. The wider memory market is covered in the 2026 memory shortage article.

What would a 24 GB RTX 5080 run that a 16 GB card cannot?

Models in the 25B to 35B range at 4-bit, with long context. The table shows how much context each model has room for after its weights. I used the GGUF file sizes on Hugging Face, the attention layout from each model's config.json, and two assumptions: 1.5 GB of runtime overhead, and marketing GB meaning GiB (24 GiB is 25.77 GB).

KV bytes per token = full-attention layers x 2 (K and V) x KV heads x head dim x 2 bytes (FP16)
Qwen3.8-27B: 16 of its 64 layers use full attention, 4 KV heads, head dim 256
             16 x 2 x 4 x 256 x 2 = 65,536 bytes = 64 KiB per token
max context  = (VRAM - 1.5 GB - weights) / KV bytes per token
24 GiB: (25.77 - 1.5 - 16.46) GB / 65,536 B = about 119,000 tokens
Model and fileWeights16 GiB card24 GiB card, FP16 KV24 GiB, q8_0 KV
gpt-oss-20b, MXFP413.79 GBabout 77k tokens131k (model maximum)131k
Qwen3.8-27B, UD-Q4_K_M16.46 GBDoes not loadabout 119kabout 224k
Gemma 4 26B-A4B, UD-Q4_K_XL17.01 GBDoes not loadLoads, 7.3 GB leftnot calculated
Qwen3.6-35B-A3B, MXFP4_MOE21.71 GBDoes not loadabout 125kabout 235k
Qwen3-32B, Q4_K_M19.76 GBDoes not loadabout 17kabout 32k
Llama 3.3 70B, Q4_K_M42.52 GBDoes not loadDoes not loadDoes not load

Weights: GGUF files in the unsloth repos on Hugging Face (Qwen3.8-27B example), checked 7 November 2026. Layer counts and KV heads from each model's config.json (Qwen3.8-27B). q8_0 KV counted at 1.0625 bytes per value. Gemma 4's config.json sets attention_k_eq_v and uses different head sizes for its global layers, so I left its KV figure out rather than guess. All rows are my calculations, not measurements.

At 16 GB the only modern model in this list with room for real context is gpt-oss-20b. At 24 GB the 27B and 35B models become usable for long documents, while dense 32B stays cramped because its KV cache is four times larger per token than Qwen3.8's hybrid layout. For per-model detail on 16 GB cards, see the best LLMs for 16 GB of VRAM. For quantization formats, see the quantization guide.

How fast would a 24 GB RTX 5080 be for LLMs?

About as fast as a 16 GB RTX 5080 on the same model, which means fast enough for one user. Decode speed is capped by memory bandwidth divided by the bytes read per token. The RTX 5080 has 960 GB/s (30 Gbps on 256 bits, per Geizhals' spec listing). The rumored 32 Gbps memory would give 1,024 GB/s, 6.7% more.

ceiling tok/s = bandwidth / weight bytes per token (dense model)
Qwen3.8-27B Q4_K_M: 1,024 GB/s / 16.46 GB = 62 tok/s ceiling

The nearest measured hardware is the RTX 5090 Laptop GPU, the same GB203 chip with 24 GB at 896 GB/s. In a llama.cpp bug report dated 11 September 2026 (issue #28790), its owner logged Qwen3.8-27B in NVFP4 (a 15.5 GB file) at 39.3 tok/s decode without speculative decoding and 50.3 to 51.7 tok/s with MTP on official builds b10917 and b10889, at a 152,000-token context with q8_0 KV. That 39.3 tok/s is 68% of the laptop's bandwidth ceiling. A desktop card with more power and bandwidth should land above it; that is an inference, not a measurement.

What would it cost?

Expect well above the rumored $999 to $1,199. That range comes from leaks summarized in November 2025, before the memory price jump. Since then the 16 GB RTX 5080 has climbed: TechSpot found the cheapest in-stock US card at $1,400 in February 2026 and $2,200 in October 2026, 120% over its $999 MSRP, with Germany at €2,100 (TechSpot, 2 November 2026). On 7 November 2026 Geizhals listed it from €1,849.99 including VAT.

TechSpot adds a theory, which it labels as such: price rises on the 16 GB card could reset the market so that a 24 GB model's launch price looks acceptable. Add the $320 to $400 of extra memory cost from the calculation above and my estimate is that a 24 GB RTX 5080 will not sell below today's 16 GB street price. If you need 32 GB instead, the RTX 5090 is the next step up, and it is in worse shape: $9,400 at its cheapest in the US in October per TechSpot, and $5,599.99 for the cheapest in-stock listing on PCPartPicker when I checked on 7 November 2026.

Should you buy now or wait for the RTX 50 Super for local AI?

Do not wait if your models already fit in 16 GB. Wait only if you specifically want 24 GB on a desktop card under about €2,500 and can live with the risk that it slips again or launches higher.

My pick for one person running local models in November 2026: buy nothing on a Super rumor. If 16 GB is too small for the model you actually use, test that model on rented 32 GB hardware first, then decide after CES 2027 whether a 24 GB RTX 5080 exists and what it costs.

FAQ

Is the RTX 5080 Super coming out?

Not confirmed. As of 7 November 2026 NVIDIA has announced no RTX 50 Super card. The latest report, from BenchLife via VideoCardz on 2 November 2026, describes a 24 GB RTX 5080 planned for Q1 2027 to replace the 16 GB model, but says board partners had not received design kits by the end of October. Treat any date as a rumor until NVIDIA announces it.

How much VRAM would the RTX 5080 Super have?

Leaks put it at 24 GB of GDDR7 on the same 256-bit bus as the RTX 5080, using eight 3 GB chips instead of eight 2 GB chips. TweakTown's summary of leaks (10 November 2025) also lists 10,752 CUDA cores, 32 Gbps memory and 415 W. None of this is confirmed by NVIDIA.

When is the RTX 50 Super release date?

There is no official date. Reports moved it from CES 2026 to Q3 2026 (HKEPC via TweakTown, November 2025), then to an indefinite hold (Board Channels, January 2026), then to a Q1 2027 window for a 24 GB RTX 5080 (BenchLife, October 2026). VideoCardz says an announcement at CES 2027, 6 to 9 January, is possible.

Is 24 GB of VRAM enough for local LLMs?

For one user on models up to about 27B to 35B parameters at 4-bit, yes. By my calculation from the Hugging Face file sizes and config.json, Qwen3.8-27B at Q4_K_M leaves room for about 119,000 tokens of FP16 KV cache in 24 GB, and does not load in 16 GB. A 70B model at 4-bit needs about 43 GB and does not fit.

Will a 24 GB RTX 5080 be cheaper than an RTX 5090?

Almost certainly, but probably not cheap. The 16 GB RTX 5080 already sold for $2,200 in the US in October 2026 (TechSpot), and the 3 GB chips reportedly cost three times as much as 2 GB chips. An RTX 5090 cost $9,400 at its cheapest in the US in October per TechSpot, and $5,599.99 at PCPartPicker's cheapest in-stock listing on 7 November.

Sources

Every figure above is attributed to its source in the sentence or table where it appears. Pages were read on 7 November 2026 unless a date says otherwise.

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