Can Leanstral 119B A6B run on AMD Instinct MI250 128GB?

YES — Runs Great

S92Excellent

Estimated from fit model

Leanstral 119B A6B needs ~96.6 GB VRAM. AMD Instinct MI250 128GB has 128.0 GB. With Q4_K_M quantization, expect ~66 tok/s.

Runtime: vLLMCapacity: RoomyBandwidth: HighStack: OptimizedBottleneck: 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) — 96.6 GB, 66.3 tok/s, Runs well

96.6 GB required128.0 GB available

75% VRAM used

Fit status

Runs well

Decode

66.3 tok/s

TTFT

2921 ms

Safe context

73K

Memory

96.6 GB / 128.0 GB

Memory breakdown

Weights72.6 GB

KV Cache8.8 GB

Runtime2.4 GB

Headroom12.8 GB

See how fast it feels

See how fast it feelsLeanstral 119B A6B 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: 66.3 tok/s decode · 2.9s TTFT (warm) · 166 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	66.3 tok/s	1593 ms	73K
Coding	S	Runs well	66.3 tok/s	2921 ms	73K
Agentic Coding	S	Tight fit	66.3 tok/s	4248 ms	73K
Reasoning	S	Runs well	66.3 tok/s	3452 ms	73K
RAG	S	Tight fit	66.3 tok/s	5310 ms	73K

Quantization options

How Leanstral 119B A6B (119B params) fits at each quantization level on AMD Instinct MI250 128GB (128.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	46.4 GB	Low	A80
Q3_K_S	3	58.3 GB	Low	A82
NVFP4	4	66.6 GB	Medium	A83
Q4_K_M	4	72.6 GB	Medium	A84
Q5_K_M	5	85.7 GB	High	A84
Q6_KBest for your GPU	6	97.6 GB	High	A84
Q8_0	8	127.3 GB	Very High	F0
F16	16	244.0 GB	Maximum	F0

Get started

Copy-paste commands to run Leanstral 119B A6B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
  --hf-repo "mistralai/Leanstral-2603" \
  --hf-file "Leanstral-2603-Q4_K_M.gguf" \
  -c 4096 -ngl 99

Your hardware

More models your AMD Instinct MI250 128GB can run

Model	Params	Grade	Decode
Devstral 2 123B Instruct	123B	S	25.2 tok/s
Qwen 3.5 122B A10B	122B	S	66.5 tok/s
Pixtral Large 124B	124B	S	25 tok/s

Frequently asked questions

Can AMD Instinct MI250 128GB run Leanstral 119B A6B?

Yes, AMD Instinct MI250 128GB can run Leanstral 119B A6B with a S grade (Runs well). Expected decode speed: 66.3 tok/s.

How much VRAM does Leanstral 119B A6B need?

Leanstral 119B A6B (119B parameters) requires approximately 96.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Leanstral 119B A6B?

The recommended quantization for Leanstral 119B A6B is Q4_K_M, which balances quality and memory efficiency.

What speed will Leanstral 119B A6B run at on AMD Instinct MI250 128GB?

On AMD Instinct MI250 128GB, Leanstral 119B A6B achieves approximately 66.3 tokens per second decode speed with a time-to-first-token of 2921ms using Q4_K_M quantization.

Can AMD Instinct MI250 128GB run Leanstral 119B A6B for coding?

For coding workloads, Leanstral 119B A6B on AMD Instinct MI250 128GB receives a S grade with 66.3 tok/s and 73K context.

What context window can Leanstral 119B A6B use on AMD Instinct MI250 128GB?

On AMD Instinct MI250 128GB, Leanstral 119B A6B can safely use up to 73K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.

See all results for AMD Instinct MI250 128GB See all hardware for Leanstral 119B A6B

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