Mac mini M4 64GBOpção econômica
64 GB Unified (+32)
B
Adds memory headroom for longer context windows and future model growth.42 tok/s decodificação
Adds memory headroom for longer context windows and future model growth.
~$1,099 MSRP
Can Granite 4.1 3B run on Radeon Pro W7800 32GB?
YES — Runs Great
B61Good
Estimated from fit model
Granite 4.1 3B needs ~7.2 GB VRAM. Radeon Pro W7800 32GB has 32.0 GB. With Q4_K_M quantization, expect ~42 tok/s.
Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: StandardBottleneck: Balanced
Operating mode
Choose the run profile you care about
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
Q4_K_M (Medium quality) — 7.2 GB, 42.0 tok/s, Runs well
7.2 GB required32.0 GB available
23% VRAM used
Fit status
Runs well
Decode
42.0 tok/s
TTFT
4610 ms
Safe context
131K
Memory
7.2 GB / 32.0 GB
Memory breakdown
Weights1.8 GB
KV Cache1.2 GB
Runtime0.9 GB
Headroom3.2 GB
See how fast it feels
See how fast it feelsGranite 4.1 3B on Radeon Pro W7800 32GB
1st promptCold start — includes initialization
>Write a Python function to sort a list
Here's a Python function that sorts a list using quicksort:
def quicksort(arr):
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quicksort(left) + middle + quicksort(right)
# Example usage
numbers = [3, 6, 8, 10, 1, 2, 1]
print(quicksort(numbers)) # [1, 1, 2, 3, 6, 8, 10]
The algorithm picks a pivot, partitions the list into smaller, equal, and larger elements, then recursively sorts each partition and concatenates the results.
2nd promptWarm — model ready, no init overhead
>Now add type hints and a docstring
def quicksort(arr: list[int]) -> list[int]:
"""Sort a list using the quicksort algorithm.
Args:
arr: List of integers to sort.
Returns:
A new sorted list.
"""
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quicksort(left) + middle + quicksort(right)
Added type hints for the input and return type, plus a Google-style docstring.
Estimated: 42.0 tok/s decode · 4.6s TTFT (warm) · 105 tok/s prefill
What limits this setup
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.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 42.0 tok/s | 2514 ms | 131K |
| Coding | B | Runs well | 42.0 tok/s | 4610 ms | 131K |
| Agentic Coding | B | Runs well | 42.0 tok/s | 6705 ms | 131K |
| Reasoning | B | Runs well | 42.0 tok/s | 5448 ms | 131K |
| RAG | B | Runs well | 42.0 tok/s | 8381 ms | 131K |
Quantization options
How Granite 4.1 3B (3B params) fits at each quantization level on Radeon Pro W7800 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.2 GB | Low | B60 |
Q3_K_S | 3 | 1.5 GB | Low | B60 |
NVFP4 | 4 | 1.7 GB | Medium | B60 |
Q4_K_M | 4 | 1.8 GB | Medium | B60 |
Q5_K_M | 5 | 2.2 GB | High | B60 |
Q6_K | 6 | 2.5 GB | High | B60 |
Q8_0 | 8 | 3.2 GB | Very High | B60 |
F16Best for your GPU | 16 | 6.1 GB | Maximum | B61 |
Get started
Copy-paste commands to run Granite 4.1 3B on your machine.
Run
ollama run granite4.1:3bOpções de upgrade
Hardware que roda bem Granite 4.1 3B
Frequently asked questions
Can Radeon Pro W7800 32GB run Granite 4.1 3B?
Yes, Radeon Pro W7800 32GB can run Granite 4.1 3B with a B grade (Runs well). Expected decode speed: 42.0 tok/s.
How much VRAM does Granite 4.1 3B need?
Granite 4.1 3B (3B parameters) requires approximately 7.2 GB of memory with Q4_K_M quantization.
What is the best quantization for Granite 4.1 3B?
The recommended quantization for Granite 4.1 3B is Q4_K_M, which balances quality and memory efficiency.
What speed will Granite 4.1 3B run at on Radeon Pro W7800 32GB?
On Radeon Pro W7800 32GB, Granite 4.1 3B achieves approximately 42.0 tokens per second decode speed with a time-to-first-token of 4610ms using Q4_K_M quantization.
Can Radeon Pro W7800 32GB run Granite 4.1 3B for coding?
For coding workloads, Granite 4.1 3B on Radeon Pro W7800 32GB receives a B grade with 42.0 tok/s and 131K context.
What context window can Granite 4.1 3B use on Radeon Pro W7800 32GB?
On Radeon Pro W7800 32GB, Granite 4.1 3B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Embed this result▼
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/granite-4.1-3b-on-radeon-pro-w7800-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: