MacBook Pro M3 Pro 18GBBudget pick
18 GB Unified (+6)
B
This setup is broadly balanced for this model.42 tok/s decode
~$1,999 MSRP
Can Granite 4.1 3B run on RTX A2000 12GB?
YES — Runs Great
B68Good
○Estimated from fit model
Granite 4.1 3B needs ~6.7 GB VRAM. RTX A2000 12GB has 12.0 GB. With Q4_K_M quantization, expect ~42 tok/s.
Runtime: vLLMCapacity: RoomyBandwidth: LowStack: OptimizedBottleneck: Balanced
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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) — 6.7 GB, 42.0 tok/s, Runs well
6.7 GB required12.0 GB available
56% VRAM used
Fit status
Runs well
Decode
42.0 tok/s
TTFT
4610 ms
Safe context
86K
Memory
6.7 GB / 12.0 GB
Memory breakdown
Weights1.8 GB
KV Cache1.2 GB
Runtime2.4 GB
Headroom1.2 GB
See how fast it feels
See how fast it feelsGranite 4.1 3B on RTX A2000 12GB
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 | 86K |
| Coding | B | Runs well | 42.0 tok/s | 4610 ms | 86K |
| Agentic Coding | A | Runs well | 42.0 tok/s | 6705 ms | 86K |
| Reasoning | B | Runs well | 42.0 tok/s | 5448 ms | 86K |
| RAG | A | Runs well | 42.0 tok/s | 8381 ms | 86K |
Quantization options
How Granite 4.1 3B (3B params) fits at each quantization level on RTX A2000 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.2 GB | Low | B64 |
Q3_K_S | 3 | 1.5 GB | Low | B65 |
NVFP4 | 4 |
Get started
Copy-paste commands to run Granite 4.1 3B on your machine.
Run
ollama run granite4.1:3bUpgrade options