Mac Studio M2 Ultra 64GBOpción económica
64 GB Unified (+24)
C
Este setup está bastante equilibrado para este modelo.102.2 tok/s decodificación
~$3,999 MSRP
Can Granite 3.1 8B run on NVIDIA A100 40GB?
YES — Runs Great
C53Usable
Estimated from fit model
Granite 3.1 8B needs ~12.0 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~112 tok/s.
Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: 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) — 12.0 GB, 112.0 tok/s, Runs well
12.0 GB required40.0 GB available
30% VRAM used
Fit status
Runs well
Decode
112.0 tok/s
TTFT
1729 ms
Safe context
128K
Memory
12.0 GB / 40.0 GB
Memory breakdown
Weights4.9 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom4.0 GB
See how fast it feels
See how fast it feelsGranite 3.1 8B on NVIDIA A100 40GB
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: 112.0 tok/s decode · 1.7s TTFT (warm) · 280 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 | C | Runs well | 112.0 tok/s | 943 ms | 128K |
| Coding | C | Runs well | 112.0 tok/s | 1729 ms | 128K |
| Agentic Coding | C | Runs well | 112.0 tok/s | 2514 ms | 128K |
| Reasoning | C | Runs well | 112.0 tok/s | 2043 ms | 128K |
| RAG | C | Runs well | 112.0 tok/s | 3143 ms | 128K |
Quantization options
How Granite 3.1 8B (8B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C47 |
Q3_K_S | 3 | 3.9 GB | Low | C47 |
NVFP4 | 4 | 4.5 GB | Medium | C47 |
Q4_K_M | 4 | 4.9 GB | Medium | C47 |
Q5_K_M | 5 | 5.8 GB | High | C47 |
Q6_K | 6 | 6.6 GB | High | C48 |
Q8_0 | 8 | 8.6 GB | Very High | C48 |
F16Best for your GPU | 16 | 16.4 GB | Maximum | C51 |
Get started
Copy-paste commands to run Granite 3.1 8B on your machine.
Run
ollama run granite3.1-denseOpciones de mejora
Hardware que ejecuta bien Granite 3.1 8B
Frequently asked questions
Can NVIDIA A100 40GB run Granite 3.1 8B?
Yes, NVIDIA A100 40GB can run Granite 3.1 8B with a C grade (Runs well). Expected decode speed: 112.0 tok/s.
How much VRAM does Granite 3.1 8B need?
Granite 3.1 8B (8B parameters) requires approximately 12.0 GB of memory with Q4_K_M quantization.
What is the best quantization for Granite 3.1 8B?
The recommended quantization for Granite 3.1 8B is Q4_K_M, which balances quality and memory efficiency.
What speed will Granite 3.1 8B run at on NVIDIA A100 40GB?
On NVIDIA A100 40GB, Granite 3.1 8B achieves approximately 112.0 tokens per second decode speed with a time-to-first-token of 1729ms using Q4_K_M quantization.
Can NVIDIA A100 40GB run Granite 3.1 8B for coding?
For coding workloads, Granite 3.1 8B on NVIDIA A100 40GB receives a C grade with 112.0 tok/s and 128K context.
What context window can Granite 3.1 8B use on NVIDIA A100 40GB?
On NVIDIA A100 40GB, Granite 3.1 8B can safely use up to 128K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
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<iframe src="https://willitrunai.com/embed/granite-3.1-8b-on-a100-40gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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