Aya Expanse 8B needs ~9.3 GB VRAM. RTX 4090 Laptop 16GB has 16.0 GB. With Q4_K_M quantization, expect ~93 tok/s.
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
Fit status
Runs well
Decode
93.4 tok/s
TTFT
2073 ms
Safe context
8K
Memory
9.3 GB / 16.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 93.4 tok/s | 1131 ms | 8K |
| Coding | B | Runs well | 93.4 tok/s | 2073 ms | 8K |
| Agentic Coding | B | Runs well | 93.4 tok/s | 3015 ms | 8K |
| Reasoning | B | Runs well | 93.4 tok/s | 2450 ms | 8K |
| RAG | B | Runs well | 93.4 tok/s | 3769 ms | 8K |
How Aya Expanse 8B (8B params) fits at each quantization level on RTX 4090 Laptop 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C49 |
Q3_K_S | 3 | 3.9 GB | Low | C49 |
NVFP4 | 4 |
Copy-paste commands to run Aya Expanse 8B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "CohereForAI/aya-expanse-8b" \
--hf-file "aya-expanse-8b-Q4_K_M.gguf" \
-c 4096 -ngl 99Yes, RTX 4090 Laptop 16GB can run Aya Expanse 8B with a B grade (Runs well). Expected decode speed: 93.4 tok/s.
Aya Expanse 8B (8B parameters) requires approximately 9.3 GB of memory with Q4_K_M quantization.
The recommended quantization for Aya Expanse 8B is Q4_K_M, which balances quality and memory efficiency.
On RTX 4090 Laptop 16GB, Aya Expanse 8B achieves approximately 93.4 tokens per second decode speed with a time-to-first-token of 2073ms using Q4_K_M quantization.
For coding workloads, Aya Expanse 8B on RTX 4090 Laptop 16GB receives a B grade with 93.4 tok/s and 8K context.
On RTX 4090 Laptop 16GB, Aya Expanse 8B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/aya-expanse-8b-on-rtx-4090-laptop-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
4.5 GB |
| Medium |
| C50 |
Q4_K_M | 4 | 4.9 GB | Medium | C50 |
Q5_K_M | 5 | 5.8 GB | High | C51 |
Q6_K | 6 | 6.6 GB | High | C52 |
Q8_0Best for your GPU | 8 | 8.6 GB | Very High | C53 |
F16 | 16 | 16.4 GB | Maximum | F0 |