RTX 3050 8GBOpção econômica8 GB VRAM (+2)224 GB/s (+32)
B
Adds memory headroom for longer context windows and future model growth.36 tok/s decodificação
Adds memory headroom for longer context windows and future model growth.
~$249 MSRP
Can Granite Code 3B run on RTX 4050 Laptop 6GB?
YES — With Offload
B68Good
Estimated from fit model
Granite Code 3B needs ~5.8 GB VRAM. RTX 4050 Laptop 6GB has 6.0 GB. With Q4_K_M quantization, expect ~48 tok/s.
Runtime: llama.cppCapacity: OffloadBandwidth: Very lowStack: StandardBottleneck: Memory bandwidth
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) — 5.8 GB, 48.0 tok/s, Runs with offload
5.8 GB required6.0 GB available
97% VRAM used
Fit status
Runs with offload
Decode
48.0 tok/s
TTFT
4033 ms
Safe context
8K
Memory
5.8 GB / 6.0 GB
Memory breakdown
Weights1.8 GB
KV Cache2.5 GB
Runtime0.9 GB
Headroom0.6 GB
See how fast it feels
See how fast it feelsGranite Code 3B on RTX 4050 Laptop 6GB
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: 48.0 tok/s decode · 4.0s TTFT (warm) · 120 tok/s prefill
What limits this setup
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Best improvement path
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 48.0 tok/s | 2200 ms | 8K |
| Coding | B | Runs with offload | 48.0 tok/s | 4033 ms | 8K |
| Agentic Coding | F | Too heavy | 26.9 tok/s | 10480 ms | 8K |
| Reasoning | B | Runs with offload | 48.0 tok/s | 4767 ms | 8K |
| RAG | F | Too heavy | 26.9 tok/s | 13100 ms | 8K |
Quantization options
How Granite Code 3B (3B params) fits at each quantization level on RTX 4050 Laptop 6GB (6.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.2 GB | Low | B69 |
Q3_K_S | 3 | 1.5 GB | Low | A70 |
NVFP4 | 4 | 1.7 GB | Medium | A71 |
Q4_K_M | 4 | 1.8 GB | Medium | A71 |
Q5_K_M | 5 | 2.2 GB | High | A71 |
Q6_K | 6 | 2.5 GB | High | A70 |
Q8_0Best for your GPU | 8 | 3.2 GB | Very High | B70 |
F16 | 16 | 6.1 GB | Maximum | F0 |
Get started
Copy-paste commands to run Granite Code 3B on your machine.
Run
ollama run granite-code:3bOpções de upgrade
Hardware que roda bem Granite Code 3B
RTX 3050 8GBOpção econômicaRTX 5060 8GBMelhor custo-benefício8 GB VRAM (+2)448 GB/s (+256)
A
Adds memory headroom for longer context windows and future model growth.57 tok/s decodificação
Adds memory headroom for longer context windows and future model growth.
~$299 MSRP
RTX 5050 8GBUpgrade NVIDIA8 GB VRAM (+2)224 GB/s (+32)
A
Adds memory headroom for longer context windows and future model growth.57 tok/s decodificação
Adds memory headroom for longer context windows and future model growth.
~$299 MSRP
Frequently asked questions
Can RTX 4050 Laptop 6GB run Granite Code 3B?
Yes, RTX 4050 Laptop 6GB can run Granite Code 3B with a B grade (Runs with offload). Expected decode speed: 48.0 tok/s.
How much VRAM does Granite Code 3B need?
Granite Code 3B (3B parameters) requires approximately 5.8 GB of memory with Q4_K_M quantization.
What is the best quantization for Granite Code 3B?
The recommended quantization for Granite Code 3B is Q4_K_M, which balances quality and memory efficiency.
What speed will Granite Code 3B run at on RTX 4050 Laptop 6GB?
On RTX 4050 Laptop 6GB, Granite Code 3B achieves approximately 48.0 tokens per second decode speed with a time-to-first-token of 4033ms using Q4_K_M quantization.
Can RTX 4050 Laptop 6GB run Granite Code 3B for coding?
For coding workloads, Granite Code 3B on RTX 4050 Laptop 6GB receives a B grade with 48.0 tok/s and 8K context.
What context window can Granite Code 3B use on RTX 4050 Laptop 6GB?
On RTX 4050 Laptop 6GB, Granite Code 3B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
What should I upgrade first if Granite Code 3B feels slow on RTX 4050 Laptop 6GB?
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
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