Aya Expanse 32B needs ~24.0 GB but RTX 5060 Ti 8GB only has 8.0 GB. Try a smaller quantization or lighter model.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
16.0 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
2.3 tok/s
TTFT
83406 ms
Safe context
4K
Memory
24.0 GB / 8.0 GB
Offload
70%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 24.0 GB, but this setup only exposes 8.0 GB of usable VRAM.
Add more VRAM headroom
The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 2.3 tok/s | 45494 ms | 4K |
| Coding | F | Too heavy | 2.3 tok/s | 83406 ms | 4K |
| Agentic Coding | F | Too heavy | 2.3 tok/s | 121317 ms | 4K |
| Reasoning | F | Too heavy | 2.3 tok/s | 98570 ms | 4K |
| RAG | F | Too heavy | 2.3 tok/s | 151646 ms | 4K |
How Aya Expanse 32B (32B params) fits at each quantization level on RTX 5060 Ti 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 12.5 GB | Low | F0 |
Q3_K_S | 3 | 15.7 GB | Low | F0 |
NVFP4 | 4 | 17.9 GB | Medium | F0 |
Q4_K_M | 4 | 19.5 GB | Medium | F0 |
Q5_K_M | 5 | 23.0 GB | High | F0 |
Q6_K | 6 | 26.2 GB | High | F0 |
Q8_0 | 8 | 34.2 GB | Very High | F0 |
F16 | 16 | 65.6 GB | Maximum | F0 |
Opciones de mejora
RTX 3090 24GBOpción económicaHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Sube la velocidad estimada de decodificación alrededor de un 943%.
~$1,499 MSRP
RTX 4090 24GBMejora NVIDIAHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Sube la velocidad estimada de decodificación alrededor de un 1117%.
~$1,599 MSRP
RTX 5090 32GBMejor relación calidad-precioHace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.
Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.
~$1,999 MSRP
No, Aya Expanse 32B requires more memory than RTX 5060 Ti 8GB provides.
Aya Expanse 32B (32B parameters) requires approximately 24.0 GB of memory with Q4_K_M quantization.
The recommended quantization for Aya Expanse 32B is Q4_K_M, which balances quality and memory efficiency.
On RTX 5060 Ti 8GB, Aya Expanse 32B achieves approximately 2.3 tokens per second decode speed with a time-to-first-token of 83406ms using Q4_K_M quantization.
For coding workloads, Aya Expanse 32B on RTX 5060 Ti 8GB receives a F grade with 2.3 tok/s and 4K context.
On RTX 5060 Ti 8GB, Aya Expanse 32B can safely use up to 4K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/aya-expanse-32b-on-rtx-5060-ti-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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