Llama 3.1 8B Instruct on NVIDIA GeForce RTX 5080
Measured this month.
Measurement
- tok/s
- 118.2
- TTFT
- 71 ms
- VRAM used
- 5.4 GB
- RAM used
- 1.3 GB
- Power
- 268 W
- Quant
- Q4_K_M
- Context
- 8K
- Run date
- 2026-05-05
- Source
- community
RTX 5080 16GB on Blackwell architecture. ~13% faster decode than RTX 4090 on the same Llama 3.1 8B Q4_K_M workload — consistent with the memory-bandwidth uplift (Blackwell's GDDR7 vs Ada's GDDR6X). The 16GB VRAM ceiling is what matters: the 5080 cannot fit 32B-class AWQ models that the 4090 can. Pick the 5080 for 8B-13B-class workloads where peak throughput matters; pick the 4090 (or 5090) when you need the VRAM headroom for larger models. Numbers triangulated from multiple community runs at NVIDIA driver 575+.
Why this confidence tier?
Confidence is rule-based. Every factor below contributed to the tier. We never expose a single numeric score; the tier label is auditable through this explanation alone.
- +Source: community submission
- Reproduce this benchmark →An independent reproduction with matching numbers lifts the tier and reduces single-source risk.
- Read the confidence methodology →Full editorial standards for tiering.
- Why we don't use percentages →Tier labels — auditable, no opaque score.
Cohort intelligence
How this measurement compares to the rest of the corpus. Only comparable rows (same model + hardware first, with relaxations labelled) are used. We never average across runtimes or quant formats unless explicitly told to.
Same model + hardware, different runtime
1 matching rowVariance here is pure runtime / version drift. Wide spread suggests a runtime regression candidate worth investigating.
- 132.2 tok/srtx-5080ollama version is 0.23.2Q4_K_MEditorial
Same model, different hardware
7 matching rowsWhat this model looks like on adjacent hardware. Drives the 'should I upgrade?' question.
- 105.0 tok/srtx-3090Q4_K_MEditorial
- 150.0 tok/srtx-4090Q4_K_MEditorial
- 86.4 tok/srx-7900-xtxQ4_K_MEditorial
- 78.5 tok/sapple-m4-maxMLX-4bitEditorial
- 78.5 tok/sapple-m4-maxMLX-4bitEditorial
- +2 more
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Related
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<a href="https://runlocalai.co/benchmarks/333" rel="noopener">RunLocalAI: Llama 3.1 8B Instruct on NVIDIA GeForce RTX 5080 — 118.2 tok/s</a>
Next recommended step
Got the same model + hardware? Run it and submit your numbers — successful reproductions lift this benchmark's confidence tier.