RTX 5070 12GBコスパ重視12 GB VRAM (+1)672 GB/s (+188)
B
Raises estimated decode speed by about 48%.86.8 tok/sデコード
Raises estimated decode speed by about 48%.
〜$549 MSRP
Can granite 8b code instruct 4k run on GTX 1080 Ti 11GB?
YES — Runs Great
B55Good
Estimated from fit model
granite 8b code instruct 4k needs ~8.1 GB VRAM. GTX 1080 Ti 11GB has 11.0 GB. With Q4_K_M quantization, expect ~59 tok/s.
Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: 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) — 8.1 GB, 58.5 tok/s, Runs well
8.1 GB required11.0 GB available
74% VRAM used
Fit status
Runs well
Decode
58.5 tok/s
TTFT
3308 ms
Safe context
65K
Memory
8.1 GB / 11.0 GB
Memory breakdown
Weights4.9 GB
KV Cache0.9 GB
Runtime1.2 GB
Headroom1.1 GB
See how fast it feels
See how fast it feelsgranite 8b code instruct 4k on GTX 1080 Ti 11GB
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: 58.5 tok/s decode · 3.3s TTFT (warm) · 146 tok/s prefill
What limits this setup
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 58.5 tok/s | 1805 ms | 65K |
| Coding | B | Runs well | 58.5 tok/s | 3308 ms | 65K |
| Agentic Coding | C | Tight fit | 58.5 tok/s | 4812 ms | 65K |
| Reasoning | B | Runs well | 58.5 tok/s | 3910 ms | 65K |
| RAG | C | Tight fit | 58.5 tok/s | 6015 ms | 65K |
Quantization options
How granite 8b code instruct 4k (8B params) fits at each quantization level on GTX 1080 Ti 11GB (11.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C50 |
Q3_K_S | 3 | 3.9 GB | Low | C51 |
NVFP4 | 4 | 4.5 GB | Medium | C52 |
Q4_K_M | 4 | 4.9 GB | Medium | C53 |
Q5_K_M | 5 | 5.8 GB | High | C52 |
Q6_KBest for your GPU | 6 | 6.6 GB | High | C52 |
Q8_0 | 8 | 8.6 GB | Very High | F0 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Get started
Copy-paste commands to run granite 8b code instruct 4k on your machine.
Run
lms load hf-ibm-granite--granite-8b-code-instruct-4k-gguf && lms server startアップグレードオプション
granite 8b code instruct 4kを快適に動かすハードウェア
RTX 5070 12GBコスパ重視RTX 4070 Super 12GBコスパ最良12 GB VRAM (+1)504 GB/s (+20)
B
Raises estimated decode speed by about 36%.79.5 tok/sデコード
Raises estimated decode speed by about 36%.
〜$599 MSRP
RTX 4070 12GBNVIDIAアップグレード12 GB VRAM (+1)504 GB/s (+20)
B
Raises estimated decode speed by about 32%.77.5 tok/sデコード
Raises estimated decode speed by about 32%.
〜$599 MSRP
Frequently asked questions
Can GTX 1080 Ti 11GB run granite 8b code instruct 4k?
Yes, GTX 1080 Ti 11GB can run granite 8b code instruct 4k with a B grade (Runs well). Expected decode speed: 58.5 tok/s.
How much VRAM does granite 8b code instruct 4k need?
granite 8b code instruct 4k (8B parameters) requires approximately 8.1 GB of memory with Q4_K_M quantization.
What is the best quantization for granite 8b code instruct 4k?
The recommended quantization for granite 8b code instruct 4k is Q4_K_M, which balances quality and memory efficiency.
What speed will granite 8b code instruct 4k run at on GTX 1080 Ti 11GB?
On GTX 1080 Ti 11GB, granite 8b code instruct 4k achieves approximately 58.5 tokens per second decode speed with a time-to-first-token of 3308ms using Q4_K_M quantization.
Can GTX 1080 Ti 11GB run granite 8b code instruct 4k for coding?
For coding workloads, granite 8b code instruct 4k on GTX 1080 Ti 11GB receives a B grade with 58.5 tok/s and 65K context.
What context window can granite 8b code instruct 4k use on GTX 1080 Ti 11GB?
On GTX 1080 Ti 11GB, granite 8b code instruct 4k can safely use up to 65K tokens of context. The model's official context limit is —, 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/hf-ibm-granite--granite-8b-code-instruct-4k-gguf-on-gtx-1080-ti-11gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: