Can Granite Code 8B run on Radeon PRO W7700 16GB?

YES — Runs Great

A79Great

Estimated from fit model

Granite Code 8B needs ~9.3 GB VRAM. Radeon PRO W7700 16GB has 16.0 GB. With Q4_K_M quantization, expect ~75 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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 9.3 GB, 74.9 tok/s, Runs well

9.3 GB required16.0 GB available

58% VRAM used

Fit status

Runs well

Decode

74.9 tok/s

TTFT

2586 ms

Safe context

Memory

9.3 GB / 16.0 GB

Memory breakdown

Weights4.9 GB

KV Cache2.0 GB

Runtime0.9 GB

Headroom1.6 GB

See how fast it feels

See how fast it feelsGranite Code 8B on Radeon PRO W7700 16GB
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: 74.9 tok/s decode · 2.6s TTFT (warm) · 187 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	A	Runs well	74.9 tok/s	1411 ms	8K
Coding	A	Runs well	74.9 tok/s	2586 ms	8K
Agentic Coding	A	Runs well	74.9 tok/s	3762 ms	8K
Reasoning	A	Runs well	74.9 tok/s	3056 ms	8K
RAG	A	Runs well	74.9 tok/s	4702 ms	8K

Quantization options

How Granite Code 8B (8B params) fits at each quantization level on Radeon PRO W7700 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	A72
Q3_K_S	3	3.9 GB	Low	A73
NVFP4	4	4.5 GB	Medium	A73
Q4_K_M	4	4.9 GB	Medium	A74
Q5_K_M	5	5.8 GB	High	A75
Q6_K	6	6.6 GB	High	A75
Q8_0Best for your GPU	8	8.6 GB	Very High	A77
F16	16	16.4 GB	Maximum	F0

Get started

Copy-paste commands to run Granite Code 8B on your machine.

Run

ollama run granite-code:8b

Your hardware

More models your Radeon PRO W7700 16GB can run

Model	Params	Grade	Decode
Qwen 3.5 9B	9B	S	66.5 tok/s
Qwen 3 14B	14B	S	43 tok/s
Phi-4-reasoning-plus 14B	14.7B	S	40.7 tok/s
GPT-OSS 20B	21B	A	39.3 tok/s
Ministral 3 14B	14B	S	42.8 tok/s

Frequently asked questions

Can Radeon PRO W7700 16GB run Granite Code 8B?

Yes, Radeon PRO W7700 16GB can run Granite Code 8B with a A grade (Runs well). Expected decode speed: 74.9 tok/s.

How much VRAM does Granite Code 8B need?

Granite Code 8B (8B parameters) requires approximately 9.3 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite Code 8B?

The recommended quantization for Granite Code 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite Code 8B run at on Radeon PRO W7700 16GB?

On Radeon PRO W7700 16GB, Granite Code 8B achieves approximately 74.9 tokens per second decode speed with a time-to-first-token of 2586ms using Q4_K_M quantization.

Can Radeon PRO W7700 16GB run Granite Code 8B for coding?

For coding workloads, Granite Code 8B on Radeon PRO W7700 16GB receives a A grade with 74.9 tok/s and 8K context.

What context window can Granite Code 8B use on Radeon PRO W7700 16GB?

On Radeon PRO W7700 16GB, Granite Code 8B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.

See all results for Radeon PRO W7700 16GB See all hardware for Granite Code 8B

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Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

74.9 tok/s

1411 ms

Coding

Runs well

74.9 tok/s

2586 ms

Agentic Coding

Runs well

74.9 tok/s

3762 ms

Reasoning

Runs well

74.9 tok/s

3056 ms

RAG

Runs well

74.9 tok/s

4702 ms

Quantization options

How Granite Code 8B (8B params) fits at each quantization level on Radeon PRO W7700 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	3.1 GB	Low	A72
Q3_K_S	3	3.9 GB	Low	A73
NVFP4	4	4.5 GB	Medium	A73
Q4_K_M	4	4.9 GB	Medium	A74
Q5_K_M	5	5.8 GB	High	A75
Q6_K	6	6.6 GB	High	A75
Q8_0Best for your GPU	8	8.6 GB	Very High	A77
F16	16	16.4 GB	Maximum	F0

Model

Params

Grade

Decode

Capabilities

Qwen 3.5 9B

66.5 tok/s

Qwen 3 14B

14B

43 tok/s

Phi-4-reasoning-plus 14B

14.7B

40.7 tok/s

GPT-OSS 20B

21B

39.3 tok/s

Ministral 3 14B

14B

42.8 tok/s

Frequently asked questions

Can Radeon PRO W7700 16GB run Granite Code 8B?

Yes, Radeon PRO W7700 16GB can run Granite Code 8B with a A grade (Runs well). Expected decode speed: 74.9 tok/s.

How much VRAM does Granite Code 8B need?

Granite Code 8B (8B parameters) requires approximately 9.3 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite Code 8B?

The recommended quantization for Granite Code 8B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite Code 8B run at on Radeon PRO W7700 16GB?

On Radeon PRO W7700 16GB, Granite Code 8B achieves approximately 74.9 tokens per second decode speed with a time-to-first-token of 2586ms using Q4_K_M quantization.

Can Radeon PRO W7700 16GB run Granite Code 8B for coding?

For coding workloads, Granite Code 8B on Radeon PRO W7700 16GB receives a A grade with 74.9 tok/s and 8K context.

What context window can Granite Code 8B use on Radeon PRO W7700 16GB?

On Radeon PRO W7700 16GB, Granite Code 8B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.