Can Qwen 3.5 27B run on AMD Instinct MI300X 192GB?

YES — Runs Great

S89Excellent

Estimated from fit model

Qwen 3.5 27B needs ~39.7 GB VRAM. AMD Instinct MI300X 192GB has 192.0 GB. With Q4_K_M quantization, expect ~271 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: 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) — 39.7 GB, 271.1 tok/s, Runs well

39.7 GB required192.0 GB available

21% VRAM used

Fit status

Runs well

Decode

271.1 tok/s

TTFT

714 ms

Safe context

131K

Memory

39.7 GB / 192.0 GB

Memory breakdown

Weights16.5 GB

KV Cache3.2 GB

Runtime0.9 GB

Headroom19.2 GB

See how fast it feels

See how fast it feelsQwen 3.5 27B on AMD Instinct MI300X 192GB
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: 271.1 tok/s decode · 714ms TTFT (warm) · 678 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	S	Runs well	271.1 tok/s	390 ms	131K
Coding	S	Runs well	271.1 tok/s	714 ms	131K
Agentic Coding	S	Runs well	271.1 tok/s	1039 ms	131K
Reasoning	S	Runs well	271.1 tok/s	844 ms	131K
RAG	S	Runs well	271.1 tok/s	1299 ms	131K

Inference speed

Qwen 3.5 27B inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for Qwen 3.5 27B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~79 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.

GPU / Mac	Memory	Quant	Speed (tok/s)	Fits?
RTX 5090 32GB	32 GB	Q4_K_M	78.7	Fits
RTX 4090 24GB	24 GB	Q4_K_M	50.2	Offloads

Quantization options

How Qwen 3.5 27B (27B params) fits at each quantization level on AMD Instinct MI300X 192GB (192.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	10.5 GB	Low	A80
Q3_K_S	3	13.2 GB	Low	A80
NVFP4	4

Get started

Copy-paste commands to run Qwen 3.5 27B on your machine.

Run

ollama run qwen3.5:27b

Your hardware

More models your AMD Instinct MI300X 192GB can run

Model	Params	Grade	Decode	Capabilities
Devstral 2 123B Instruct	123B	S	59.9 tok/s
Qwen3-Coder 30B A3B Instruct	30.5B	S

Frequently asked questions

Can AMD Instinct MI300X 192GB run Qwen 3.5 27B?

Yes, AMD Instinct MI300X 192GB can run Qwen 3.5 27B with a S grade (Runs well). Expected decode speed: 271.1 tok/s.

How much VRAM does Qwen 3.5 27B need?

Qwen 3.5 27B (27B parameters) requires approximately 39.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3.5 27B?

The recommended quantization for Qwen 3.5 27B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3.5 27B run at on AMD Instinct MI300X 192GB?

On AMD Instinct MI300X 192GB, Qwen 3.5 27B achieves approximately 271.1 tokens per second decode speed with a time-to-first-token of 714ms using Q4_K_M quantization.

Can AMD Instinct MI300X 192GB run Qwen 3.5 27B for coding?

For coding workloads, Qwen 3.5 27B on AMD Instinct MI300X 192GB receives a S grade with 271.1 tok/s and 131K context.

What context window can Qwen 3.5 27B use on AMD Instinct MI300X 192GB?

On AMD Instinct MI300X 192GB, Qwen 3.5 27B can safely use up to 131K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

See all results for AMD Instinct MI300X 192GB See all hardware for Qwen 3.5 27B

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