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RTX 5080 for local LLMs

3 measured results from 2 builds, each linked to its source.

Memory16 GB per card
Memory bandwidth960 GB/s (memory bandwidth as listed on llamabench)
Typical EU price≈€1,599 new (Inno3D GeForce RTX 5080 X3 16 GB GDDR7, billiger.de, 2026-10-16)

Can it run? Qwen3.8 Flash-Next on 2x RTX 5080 gpt-oss 20B on RTX 5080

All builds with the RTX 5080

BuildGPU(s)Memory GB (total)Results
Dual RTX 5080 on EPYC 7F52 (capy-flash user report)2x RTX 5080 16 GB322
Single RTX 5080 16GBRTX 5080161

All measured results

(MTP, DFlash, DSpark and similar draft-and-verify methods give much higher tok/s on predictable text and are not comparable 1:1 with plain decode)

ModelBuildRan onQuantEnginetok/sDetails
Qwen3.8 Flash-NextDual RTX 5080 on EPYC 7F52 (capy-flash user report)2x RTX 5080NVFP4capy-flash v0.7.2, --expert-cpu-threads 15, agentic decode144.4📏 User-reported (issue #11), listed in the capy-flash READMEpartly in system RAM
Qwen3.8 Flash-NextDual RTX 5080 on EPYC 7F52 (capy-flash user report)2x RTX 5080NVFP4capy-flash v0.7.2 (CUDA 13.4), agentic decode141.3📏 User-reported (issue #11), listed in the capy-flash READMEpartly in system RAM
gpt-oss 20BSingle RTX 5080 16GBRTX 5080MXFP4llama.cpp204.85

All RTX 5080 builds: see also all GPUs · best LLMs by memory size · download the dataset.

FAQ

How fast is the RTX 5080 for local LLMs?

The fastest plain-decode result we have is 204.85 tok/s on gpt-oss 20B (MXFP4, llama.cpp) in Single RTX 5080 16GB. Speed depends heavily on the model, quant and engine, so compare like with like in the table. RigBase lists 3 measured results from 2 builds.

How much memory does the RTX 5080 have?

16 GB per card. Memory bandwidth: 960 GB/s (memory bandwidth as listed on llamabench).

Which models have been measured on the RTX 5080?

Qwen3.8 Flash-Next, gpt-oss 20B.

Where do these numbers come from?

Every row links to a build page with its original public source (benchmark logs, READMEs, forum posts). RigBase does not re-run the benchmarks. Results marked ⚡ use speculative decoding and are not comparable 1:1 with plain decode.

Not enough VRAM? Rent before you buy. Run RTX 5080-class models on a rented 24–96 GB cloud GPU by the hour and see the real speed before spending €1,000+. Try it on Runpod
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