Will It Run AI

Can Qwen 3.6 27B run on AMD Instinct MI250 128GB?

YES — Runs Great

S89Excellent
Estimated from fit model

Qwen 3.6 27B needs ~31.1 GB VRAM. AMD Instinct MI250 128GB has 128.0 GB. With Q4_K_M quantization, expect ~89 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced
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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) 31.1 GB, 88.9 tok/s, Runs well
31.1 GB required128.0 GB available
24% VRAM used

Fit status

Runs well

Decode

88.9 tok/s

TTFT

2177 ms

Safe context

262K

Memory

31.1 GB / 128.0 GB

Memory breakdown

Weights16.5 GB
KV Cache1.0 GB
Runtime0.9 GB
Headroom12.8 GB

See how fast it feels

See how fast it feelsQwen 3.6 27B on AMD Instinct MI250 128GB
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: 88.9 tok/s decode · 2.2s TTFT (warm) · 222 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

WorkloadGradeFitDecodeTTFTContext
ChatSRuns well88.9 tok/s1187 ms262K
CodingSRuns well88.9 tok/s2177 ms262K
Agentic CodingSRuns well88.9 tok/s3166 ms262K
ReasoningSRuns well88.9 tok/s2572 ms262K
RAGSRuns well88.9 tok/s3957 ms262K

Quantization options

How Qwen 3.6 27B (27B params) fits at each quantization level on AMD Instinct MI250 128GB (128.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
10.5 GB
LowA81
Q3_K_S
3
13.2 GB
LowA81
NVFP4
4
15.1 GB
MediumA81
Q4_K_M
4
16.5 GB
MediumA81
Q5_K_M
5
19.4 GB
HighA81
Q6_K
6
22.1 GB
HighA82
Q8_0
8
28.9 GB
Very HighA83
F16Best for your GPU
16
55.4 GB
MaximumS87

Get started

Copy-paste commands to run Qwen 3.6 27B on your machine.

Run

lms load Qwen3.6-27B && lms server start

Your hardware

More models your AMD Instinct MI250 128GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BS31.5 tok/s
AlibabaQwen3-Coder 30B A3B Instruct30.5BS329 tok/s

Frequently asked questions

Can AMD Instinct MI250 128GB run Qwen 3.6 27B?

Yes, AMD Instinct MI250 128GB can run Qwen 3.6 27B with a S grade (Runs well). Expected decode speed: 88.9 tok/s.

How much VRAM does Qwen 3.6 27B need?

Qwen 3.6 27B (27B parameters) requires approximately 31.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Qwen 3.6 27B?

The recommended quantization for Qwen 3.6 27B is Q4_K_M, which balances quality and memory efficiency.

What speed will Qwen 3.6 27B run at on AMD Instinct MI250 128GB?

On AMD Instinct MI250 128GB, Qwen 3.6 27B achieves approximately 88.9 tokens per second decode speed with a time-to-first-token of 2177ms using Q4_K_M quantization.

Can AMD Instinct MI250 128GB run Qwen 3.6 27B for coding?

For coding workloads, Qwen 3.6 27B on AMD Instinct MI250 128GB receives a S grade with 88.9 tok/s and 262K context.

What context window can Qwen 3.6 27B use on AMD Instinct MI250 128GB?

On AMD Instinct MI250 128GB, Qwen 3.6 27B can safely use up to 262K tokens of context. The model's official context limit is 262K, but available memory constrains the safe maximum.

See all results for AMD Instinct MI250 128GBSee all hardware for Qwen 3.6 27B
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