aya expanse 8b orthogonal heretic needs ~7.8 GB VRAM. GTX 1070 8GB has 8.0 GB. With Q4_K_M quantization, expect ~31 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
31.0 tok/s
TTFT
6255 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.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
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 | 31.0 tok/s | 3412 ms | 19K |
| Coding | C | Runs with offload | 31.0 tok/s | 6255 ms | 19K |
| Agentic Coding | D | Very compromised (needs ~0.4 GB host RAM) | 18.5 tok/s | 15205 ms | 19K |
| Reasoning | C | Runs with offload | 31.0 tok/s | 7392 ms | 19K |
| RAG | D | Very compromised (needs ~0.4 GB host RAM) | 18.5 tok/s | 19007 ms | 19K |
How aya expanse 8b orthogonal heretic (8B params) fits at each quantization level on GTX 1070 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 económicaSube la velocidad estimada de decodificación alrededor de un 57%.
Añade 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 84%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$449 MSRP
RTX 4060 Ti 16GBMejora NVIDIASube la velocidad estimada de decodificación alrededor de un 39%.
Añade margen de memoria para más contexto y para que el modelo envejezca mejor.
~$499 MSRP
Yes, GTX 1070 8GB can run aya expanse 8b orthogonal heretic with a C grade (Runs with offload). Expected decode speed: 31.0 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 GTX 1070 8GB, aya expanse 8b orthogonal heretic achieves approximately 31.0 tokens per second decode speed with a time-to-first-token of 6255ms using Q4_K_M quantization.
For coding workloads, aya expanse 8b orthogonal heretic on GTX 1070 8GB receives a C grade with 31.0 tok/s and 19K context.
On GTX 1070 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.
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