RX 9070 XT vs RTX 5080 for Local AI

1. 30-second verdict

This is a same-capacity, different-price comparison — both cards carry 16 GB of discrete VRAM, so neither unlocks larger models than the other. The RTX 5080 (Blackwell, GB203, 2025) records GDDR7 at 960 GB/s on a 256-bit bus, 10,752 CUDA cores, PCIe 5.0 x16, 360 W, launch MSRP $999. The RX 9070 XT (AMD Radeon, RDNA 4, Navi 48, 2025) records GDDR6 at 640 GB/s on a 256-bit bus, 4,096 stream processors, PCIe 5.0 x16, 304 W, launch MSRP $599 (vendor spec pages). The 5080 holds a calculated 50% bandwidth advantage (960 / 640) and every sourced benchmark row in this pair: Qwen3-8B Q4_K_XL llama.cpp CUDA 12.8 at 94.14 tok/s (hardware-corner.net, 2025-12-09), a Llama-3.1-8B Q4_K_M row at 132 tok/s generation, and a tier-2 UL Procyon suite. The 9070 XT has no benchmark row on any stack — there is no same-lab pair, so no speed winner is declared. The 9070 XT is $400 cheaper at launch MSRP and 56 W lower TDP. Street price is not yet measured on either card. If your models fit 16 GB, this is a speed-and-stack decision on a $400 price gap, not a capacity decision.

2. Memory architecture

Both cards are discrete VRAM, not unified memory. Addressable GPU memory equals physical VRAM: 16 GB on both. Both record a 256-bit bus, so the bandwidth gap is pure memory speed: GDDR7 at 960 GB/s on the 5080 versus GDDR6 at 640 GB/s on the 9070 XT — a calculated 50% advantage for the Blackwell card (960 / 640, from recorded specifications). ECC is not recorded for either card. Neither card records NVLink support. Two of either card stay 2×16 GB unless a runtime shards; dual-card tok/s is not yet measured here.

3. Model-fit table

Fit labels use ai_models calculated min/recommended configs plus discrete VRAM from the product records. They are capacity checks, not speed claims.

Both cards land on the same side of every fit line — same capacity means same fit. 8B-class models fit with headroom; 14B-class models sit at the calculated 16 GB+ min and fit on both; 24B+ models fit on neither. The difference between them is bandwidth, stack, price, and power, not which models load.

4. Direct benchmark table

Only non-quarantined benchmarks rows. A blank cell means no sourced row for that card — not zero. Estimate means is_estimate=1. Do not treat one-sided rows as a pair.

Every row in this table is one-sided on the NVIDIA card. The RX 9070 XT has no benchmark row on any stack (CUDA does not apply; ROCm/Vulkan rows are not yet measured). There is no same-lab pair, so this page does not ratio any 5080 number against the 9070 XT or declare a speed winner. The Procyon suite is internally comparable (same lab platform, same driver) across its own models, but it is not a cross-vendor pair. The Llama-3.1-8B prompt figure is labeled approximate by its own source row.

5. Runtime compatibility

The two cards do not share a software stack. The 5080 is an NVIDIA CUDA discrete GPU (sourced stacks in our rows: llama.cpp CUDA 12.8, ComfyUI, UL Procyon TensorRT). The 9070 XT is an AMD discrete GPU — CUDA does not apply; local-LLM stacks run via ROCm or Vulkan backends (llama.cpp ships Vulkan/ROCm builds). A CUDA or TensorRT row is not directly comparable to a Vulkan/ROCm row even when one is measured, so cross-stack parity is not assumed. Both cards record PCIe 5.0 x16. Fine-tune / multi-adapter stacks beyond the sourced rows are not yet measured on this pair.

6. Quantization compatibility

The sourced generation rows use Q4_K_XL (Qwen3-8B, 5080) and Q4_K_M (Llama-3.1-8B, 5080) plus FP16/INT8 on the Procyon image rows. No quant row exists for the 9070 XT on any stack. Q5/Q6/Q8 decode on this pair is not yet measured. Capacity is identical at 16 GB, so quant choice changes fit identically on both cards — the 5080's GDDR7 bandwidth advantage would show up at every quant level the DB rows cover, but no sourced row exists to quantify it on this pair.

7. Max practical context examples

The sourced llama.cpp llama-bench row uses 16K context (Qwen3-8B, 5080). Qwen 3 8B native context in our model record is 40,960 tokens; Llama 3.1 8B native context is 131,072 tokens. Whether either GPU holds the full native window at a given quant is not yet measured here. Both cards have the same 16 GB, so context headroom is the same on both — bandwidth helps long-context decode speed, but no sourced long-context row exists on either card.

8. Power

Specifications record 304 W TDP (RX 9070 XT) and 360 W TDP (RTX 5080) from the vendor spec pages. The 56 W difference is rated board power, not an inference-consumption measurement. Both are single-card, desktop-class power envelopes; plan PSU headroom above TDP and check partner board power input requirements. Energy cost per million tokens is not yet measured (no watt-hour rows on either card).

9. Current price

Price class is launch_msrp only. Products table: RX 9070 XT $599 (price_checked_at 2026-09-02), RTX 5080 $999 (price_checked_at 2026-09-02). street_price_usd is NULL on both. No product_offers rows exist for either SKU. Check live listings rather than treating MSRP as street:

• RX 9070 XT current listing (affiliate)
• RTX 5080 current listing (affiliate)
• RX 9070 XT product page · RTX 5080 product page

10. Used price

Not yet measured. No used-condition offer rows exist for either SKU. Both launched in 2025, so any used pool is still young — this page will not invent a median. A discounted used 5080 can be the right buy if the CUDA stack and bandwidth matter more than the launch-price gap; a discounted 9070 XT is the right buy when 16 GB capacity at the lower price class matters more than sourced CUDA throughput.

11. Performance per current dollar

Only one side is sourced, so a full price/perf ratio is not calculable on this pair. The 5080's sourced Qwen3-8B row gives 94.14 tok/s ÷ $999 = 0.094 tok/s per launch-MSRP dollar (calculated, labeled). The 9070 XT has no sourced tok/s row, so no comparable figure exists — it is not zero, it is not-yet-measured. Because the two cards sit $400 apart at launch pricing, any future same-stack tok/s row on the 9070 XT would be directly price-comparable at launch pricing and is the single most useful missing measurement for this pair. No street or offer rows exist to recompute either figure at current prices.

12. Multi-GPU considerations

Neither card records NVLink support in the database. Desktop cards in this class have no NVLink bridge — two of either card are 2×16 GB, not one pooled pool, unless the runtime shards (tensor parallel / pipeline / expert offload). Dual-card tok/s for this pair is not yet measured. Mixing one AMD and one NVIDIA card in one runtime is generally not supported for a single model shard. Related: multi-GPU guide, workstations.

13. System requirements

Both: PCIe 5.0 x16 slot, single desktop-class board (vendor spec pages). 9070 XT: 304 W TDP. 5080: 360 W TDP. Both are backwards-compatible with PCIe 4.0 motherboards and fit a standard desktop case and a PSU with headroom above TDP. The 5080's 360 W rating is the tighter PSU constraint of the two. CPU/RAM pairing for these two SKUs is not yet measured on this page.

14. Who should buy the RX 9070 XT

• Anyone whose largest model fits 16 GB and who does not want to pay the $400 launch-price step to the 5080 ($599 vs $999).
• Anyone on an ROCm or Vulkan local-LLM stack — CUDA does not apply to this card, and every 5080 benchmark row here is CUDA/TensorRT, so none of them is a cross-stack comparison.
• Buyers who want the 56 W lower rated board power (304 W vs 360 W) at the same 256-bit bus width and same 16 GB capacity.
• Not a substitute for a 20 GB+ or 24 GB+ card when the model-fit min exceeds 16 GB (Mistral Small 24B, Gemma 3 27B).

15. Who should buy the RTX 5080

• Anyone on a CUDA/TensorRT stack (llama.cpp CUDA, ComfyUI, UL Procyon workflows) who wants sourced numbers instead of none — 94.14 tok/s on Qwen3-8B Q4_K_XL (hardware-corner.net, 2025-12-09) and the tier-2 Procyon suite.
• Buyers who want the calculated 50% memory-bandwidth advantage (GDDR7 960 GB/s vs GDDR6 640 GB/s on the same 256-bit bus), 10,752 CUDA cores, and Blackwell platform features (DLSS 4 Frame Generation listed on the NVIDIA 50-series product page — a display/gaming capability, not an AI-inference metric).
• Not a capacity pick over the 9070 XT — both are 16 GB. If you need more than 16 GB, neither card helps.

16. Evidence / source table

17. Data freshness date

Frequently asked questions

Is the RX 9070 XT better than the RTX 5080 for AI?

Both carry 16 GB of discrete VRAM, so neither unlocks larger models than the other — this is not a capacity comparison. The RTX 5080 records GDDR7 at 960 GB/s versus GDDR6 at 640 GB/s, a calculated 50% bandwidth advantage, 10,752 CUDA cores versus 4,096 stream processors, and it holds every sourced benchmark row in this pair: Qwen3-8B Q4_K_XL at 94.14 tok/s (llama.cpp llama-bench CUDA 12.8, hardware-corner.net, 2025-12-09) plus a tier-2 UL Procyon suite. The RX 9070 XT has no benchmark row on any stack, so no same-lab pair exists and this page does not invent one. The trade is price: $999 against $599 launch MSRP, and power, 360 W against 304 W.

Which GPU is faster for local LLM inference?

Only one side is measured. The RTX 5080 has sourced rows: Qwen3-8B Q4_K_XL at 94.14 tok/s (llama.cpp llama-bench CUDA 12.8, 16K context, batch 1, hardware-corner.net, 2025-12-09, tier 3, is_estimate=0) and a Llama-3.1-8B Q4_K_M row at 132 tok/s generation / 5,200 tok/s prompt (llama.cpp via Ollama, localaimaster.com, 2026-08-01, tier 3). The RX 9070 XT has no benchmark row in our database on any stack (CUDA does not apply; ROCm/Vulkan rows are not yet measured). There is no same-lab pair, so no speed winner can be declared. The 5080 does hold a calculated 50% memory-bandwidth advantage (960 vs 640 GB/s from recorded specs), which typically helps decode speed, but no sourced row confirms the delta on this pair.

What do these cards cost?

The recorded launch MSRPs differ by $400: RX 9070 XT $599, RTX 5080 $999 (products.msrp_usd, both price_checked_at 2026-09-02). street_price_usd is NULL on both and no product_offers rows exist. Treat launch MSRP as a price class, not a street quote, and check live listings.

Which GPU uses more power?

The RTX 5080. Specifications record 360 W TDP for the RTX 5080 and 304 W TDP for the RX 9070 XT (vendor spec pages). The 56 W difference is rated board power, not a measurement of inference consumption. Energy cost per million tokens is not yet measured on either card.

Does the RX 9070 XT support CUDA?

No. The RX 9070 XT is an AMD Radeon GPU; CUDA is NVIDIA-only. Local-LLM stacks on the 9070 XT run via ROCm, Vulkan, or OpenCL backends. Every sourced benchmark row in this pair is a CUDA or TensorRT run on the 5080, so none of them is directly comparable to a future Vulkan/ROCm run on the 9070 XT. This page does not assume cross-stack parity.

Should I upgrade from RX 9070 XT to RTX 5080?

You are not buying capacity — both cards hold 16 GB. You are buying a calculated 50% bandwidth increase (960 vs 640 GB/s), 10,752 CUDA cores versus 4,096 stream processors, and the only sourced benchmark rows in this pair, for $400 more at launch MSRP ($999 vs $599) and 56 W more rated power (360 W vs 304 W). If your models already fit 16 GB, the case for the upgrade is speed and CUDA stack support, not VRAM. If the $400 gap does not pay back in your workflow, the 9070 XT delivers the same capacity class at a lower launch price.

Related: best GPU for local LLMs, best GPU for deep learning, RX 9070 vs RTX 5070, RX 9070 XT vs RTX 5070 Ti, RTX 5080 vs RTX 4090, RTX 5090 vs RTX 5080, RTX 5070 vs RTX 5070 Ti, RX 9070 XT product page, RTX 5080 product page, GPU index, Can it run?.