aya expanse 8b orthogonal heretic needs ~7.8 GB VRAM. RTX 4060 Laptop 8GB has 8.0 GB. With Q4_K_M quantization, expect ~39 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 with offload
Decode
39.3 tok/s
TTFT
4921 ms
Safe context
19K
Memory
7.8 GB / 8.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Tight fit | 39.3 tok/s | 2684 ms | 19K |
| Coding | C | Runs with offload | 39.3 tok/s | 4921 ms | 19K |
| Agentic Coding | D | Very compromised (needs ~0.4 GB host RAM) | 24.4 tok/s | 11538 ms | 19K |
| Reasoning | C | Runs with offload | 39.3 tok/s | 5815 ms | 19K |
| RAG | D | Very compromised (needs ~0.4 GB host RAM) | 24.4 tok/s | 14423 ms | 19K |
How aya expanse 8b orthogonal heretic (8B params) fits at each quantization level on RTX 4060 Laptop 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C53 |
Q3_K_S | 3 | 3.9 GB | Low | C53 |
NVFP4 | 4 | 4.5 GB | Medium | C53 |
Q4_K_MBest for your GPU | 4 | 4.9 GB | Medium | C52 |
Q5_K_M | 5 | 5.8 GB | High | F0 |
Q6_K | 6 | 6.6 GB | High | F0 |
Q8_0 | 8 | 8.6 GB | Very High | F0 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Copy-paste commands to run aya expanse 8b orthogonal heretic on your machine.
Run
lms load hf-mradermacher--aya-expanse-8b-orthogonal-heretic-gguf && lms server startOpciones de mejora
RTX 3060 12GBOpción económicaAñade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$329 MSRP
RTX 5060 Ti 16GBMejor relación calidad-precioSube la velocidad estimada de decodificación alrededor de un 45%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$449 MSRP
RTX 5070 12GBMejora NVIDIASube la velocidad estimada de decodificación alrededor de un 121%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$549 MSRP
Yes, RTX 4060 Laptop 8GB can run aya expanse 8b orthogonal heretic with a C grade (Runs with offload). Expected decode speed: 39.3 tok/s.
aya expanse 8b orthogonal heretic (8B parameters) requires approximately 7.8 GB of memory with Q4_K_M quantization.
The recommended quantization for aya expanse 8b orthogonal heretic is Q4_K_M, which balances quality and memory efficiency.
On RTX 4060 Laptop 8GB, aya expanse 8b orthogonal heretic achieves approximately 39.3 tokens per second decode speed with a time-to-first-token of 4921ms using Q4_K_M quantization.
For coding workloads, aya expanse 8b orthogonal heretic on RTX 4060 Laptop 8GB receives a C grade with 39.3 tok/s and 19K context.
On RTX 4060 Laptop 8GB, aya expanse 8b orthogonal heretic can safely use up to 19K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Paste this snippet into any page to show a live fit card.
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