Can Mistral Small 4 119B run on AMD Instinct MI250X 128GB?

YES — Runs Great

S97Excellent

Estimated from fit model

Mistral Small 4 119B needs ~91.7 GB VRAM. AMD Instinct MI250X 128GB has 128.0 GB. With Q4_K_M quantization, expect ~109 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) — 91.7 GB, 108.8 tok/s, Runs well

91.7 GB required128.0 GB available

72% VRAM used

Fit status

Runs well

Decode

108.8 tok/s

TTFT

1779 ms

Safe context

124K

Memory

91.7 GB / 128.0 GB

Memory breakdown

Weights72.6 GB

KV Cache5.4 GB

Runtime0.9 GB

Headroom12.8 GB

See how fast it feels

See how fast it feelsMistral Small 4 119B on AMD Instinct MI250X 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: 108.8 tok/s decode · 1.8s TTFT (warm) · 272 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	108.8 tok/s	971 ms	124K
Coding	S	Runs well	108.8 tok/s	1779 ms	124K
Agentic Coding	S	Runs well	108.8 tok/s	2588 ms	124K
Reasoning	S	Runs well	108.8 tok/s	2103 ms	124K
RAG	S	Runs well	108.8 tok/s	3235 ms	124K

Quantization options

How Mistral Small 4 119B (119B params) fits at each quantization level on AMD Instinct MI250X 128GB (128.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	46.4 GB	Low	A85
Q3_K_S	3	58.3 GB	Low	S87
NVFP4	4	66.6 GB	Medium	S88
Q4_K_M	4	72.6 GB	Medium	S88
Q5_K_M	5	85.7 GB	High	S88
Q6_KBest for your GPU	6	97.6 GB	High	S88
Q8_0	8	127.3 GB	Very High	F0
F16	16	244.0 GB	Maximum	F0

Get started

Copy-paste commands to run Mistral Small 4 119B on your machine.

Run

lms load Mistral-Small-4-119B-2603 && lms server start

Your hardware

More models your AMD Instinct MI250X 128GB can run

Model	Params	Grade	Decode	Capabilities
Devstral 2 123B Instruct	123B	S	36.2 tok/s
Qwen 3.5 122B A10B	122B	S	100.3 tok/s

Frequently asked questions

Can AMD Instinct MI250X 128GB run Mistral Small 4 119B?

Yes, AMD Instinct MI250X 128GB can run Mistral Small 4 119B with a S grade (Runs well). Expected decode speed: 108.8 tok/s.

How much VRAM does Mistral Small 4 119B need?

Mistral Small 4 119B (119B parameters) requires approximately 91.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Mistral Small 4 119B?

The recommended quantization for Mistral Small 4 119B is Q4_K_M, which balances quality and memory efficiency.

What speed will Mistral Small 4 119B run at on AMD Instinct MI250X 128GB?

On AMD Instinct MI250X 128GB, Mistral Small 4 119B achieves approximately 108.8 tokens per second decode speed with a time-to-first-token of 1779ms using Q4_K_M quantization.

Can AMD Instinct MI250X 128GB run Mistral Small 4 119B for coding?

For coding workloads, Mistral Small 4 119B on AMD Instinct MI250X 128GB receives a S grade with 108.8 tok/s and 124K context.

What context window can Mistral Small 4 119B use on AMD Instinct MI250X 128GB?

On AMD Instinct MI250X 128GB, Mistral Small 4 119B can safely use up to 124K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.

See all results for AMD Instinct MI250X 128GB See all hardware for Mistral Small 4 119B

Embed this result▼

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/mistral-small-4-119b-on-instinct-mi250x-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: