Written by Jakub Rusinowski · Last updated October 8, 2024
Yes — comfortably
Yes, comfortably — Aya Expanse 8B at Q8_0 needs about 10.4 GB of the 16 GB usable on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM), leaving ~5.6 GB spare and running at ~67.4 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~67.4 tok/s
| Usable memory for models | 16 GB |
| Memory bandwidth | 960 GB/s |
| Form factor | Desktop |
| Operating system | Windows or Linux |
| Memory upgradeable | Yes |
| Quant | Memory needed | Fits 16 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 17.9 GB | ✗ No | — | — | 16.1 GB |
| Q8_0 | 10.4 GB | ✓ Yes | 8K | ~67.4 tok/s | 8.5 GB |
| Q6_K | 8.5 GB | ✓ Yes | 8K | ~82.4 tok/s | 6.6 GB |
| Q5_K_M | 7.6 GB | ✓ Yes | 8K | ~91.8 tok/s | 5.7 GB |
| Q4_K_M | 6.7 GB | ✓ Yes | 8K | ~102.8 tok/s | 4.8 GB |
| Q3_K_M | 5.3 GB | ✓ Yes | 8K | ~129.1 tok/s | 3.4 GB |
| Q2_K | 4.5 GB | ✓ Yes | 8K | ~150.2 tok/s | 2.6 GB |
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Aya Expanse 32B | 21.6 GB | ✗ Too large | — |
| Aya Expanse 8B | 6.7 GB | ✓ Fits | ~102.8 tok/s |
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
Yes, comfortably — Aya Expanse 8B at Q8_0 needs about 10.4 GB of the 16 GB usable on RTX 5080 Desktop (16 GB VRAM, 32 GB RAM), leaving ~5.6 GB spare and running at ~67.4 tok/s (estimated), with room for about 8,192 tokens of context.
Q8_0 — it needs about 10.4 GB of the 16 GB available, downloads as roughly 8.5 GB, and runs at an estimated 67.4 tokens/sec with up to 8K of context.
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Ollama or llama.cpp (CUDA/ROCm) — vLLM if you need concurrent serving
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