MacBook Pro M4 Max 48GBBudget pick
48 GB Unified (+16)
C
This setup is broadly balanced for this model.76.8 tok/s decode
~$2,499 MSRP
aya expanse 8b orthogonal heretic i1 needs ~9.9 GB VRAM. Radeon AI PRO R9700 32GB has 32.0 GB. With Q4_K_M quantization, expect ~77 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
77.4 tok/s
TTFT
2502 ms
Safe context
393K
Memory
9.9 GB / 32.0 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 | 77.4 tok/s | 1365 ms | 393K |
| Coding | C | Runs well | 77.4 tok/s | 2502 ms | 393K |
| Agentic Coding | C | Runs well | 77.4 tok/s | 3639 ms | 393K |
| Reasoning | C | Runs well | 77.4 tok/s | 2957 ms | 393K |
| RAG | C | Runs well | 77.4 tok/s | 4549 ms | 393K |
How aya expanse 8b orthogonal heretic i1 (8B params) fits at each quantization level on Radeon AI PRO R9700 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C43 |
Q3_K_S | 3 | 3.9 GB | Low | C43 |
NVFP4 | 4 | 4.5 GB | Medium | C43 |
Q4_K_M | 4 | 4.9 GB | Medium | C43 |
Q5_K_M | 5 | 5.8 GB | High | C44 |
Q6_K | 6 | 6.6 GB | High | C44 |
Q8_0 | 8 | 8.6 GB | Very High | C45 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | C49 |
Copy-paste commands to run aya expanse 8b orthogonal heretic i1 on your machine.
Run
lms load hf-mradermacher--aya-expanse-8b-orthogonal-heretic-i1-gguf && lms server startUpgrade options
~$2,499 MSRP
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, Radeon AI PRO R9700 32GB can run aya expanse 8b orthogonal heretic i1 with a C grade (Runs well). Expected decode speed: 77.4 tok/s.
aya expanse 8b orthogonal heretic i1 (8B parameters) requires approximately 9.9 GB of memory with Q4_K_M quantization.
The recommended quantization for aya expanse 8b orthogonal heretic i1 is Q4_K_M, which balances quality and memory efficiency.
On Radeon AI PRO R9700 32GB, aya expanse 8b orthogonal heretic i1 achieves approximately 77.4 tokens per second decode speed with a time-to-first-token of 2502ms using Q4_K_M quantization.
For coding workloads, aya expanse 8b orthogonal heretic i1 on Radeon AI PRO R9700 32GB receives a C grade with 77.4 tok/s and 393K context.
On Radeon AI PRO R9700 32GB, aya expanse 8b orthogonal heretic i1 can safely use up to 393K tokens of context. The model's official context limit is —, 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/hf-mradermacher--aya-expanse-8b-orthogonal-heretic-i1-gguf-on-radeon-ai-pro-r9700-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: