Can Codestral 22B v0.1 IMat run on AMD Instinct MI300A 128GB?

YES — Runs Great

C46Usable
Estimated from fit model

Codestral 22B v0.1 IMat needs ~29.7 GB VRAM. AMD Instinct MI300A 128GB has 128.0 GB. With Q4_K_M quantization, expect ~277 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) 29.7 GB, 276.5 tok/s, Runs well
29.7 GB required128.0 GB available
23% VRAM used

Fit status

Runs well

Decode

276.5 tok/s

TTFT

700 ms

Safe context

626K

Memory

29.7 GB / 128.0 GB

Memory breakdown

Weights13.4 GB
KV Cache2.6 GB
Runtime0.9 GB
Headroom12.8 GB

See how fast it feels

See how fast it feelsCodestral 22B v0.1 IMat on AMD Instinct MI300A 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: 276.5 tok/s decode · 700ms TTFT (warm) · 691 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
ChatCRuns well276.5 tok/s382 ms626K
CodingCRuns well276.5 tok/s700 ms626K
Agentic CodingCRuns well276.5 tok/s1019 ms626K
ReasoningCRuns well276.5 tok/s828 ms626K
RAGCRuns well276.5 tok/s1273 ms626K

Quantization options

How Codestral 22B v0.1 IMat (22B params) fits at each quantization level on AMD Instinct MI300A 128GB (128.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
8.6 GB
LowD38
Q3_K_S
3
10.8 GB
LowD38
NVFP4
4
12.3 GB
MediumD38
Q4_K_M
4
13.4 GB
MediumD38
Q5_K_M
5
15.8 GB
HighD38
Q6_K
6
18.0 GB
HighD38
Q8_0
8
23.5 GB
Very HighD39
F16Best for your GPU
16
45.1 GB
MaximumC43

Get started

Copy-paste commands to run Codestral 22B v0.1 IMat on your machine.

Run

lms load hf-legraphista--codestral-22b-v0-1-imat-gguf && lms server start

Frequently asked questions

Can AMD Instinct MI300A 128GB run Codestral 22B v0.1 IMat?

Yes, AMD Instinct MI300A 128GB can run Codestral 22B v0.1 IMat with a C grade (Runs well). Expected decode speed: 276.5 tok/s.

How much VRAM does Codestral 22B v0.1 IMat need?

Codestral 22B v0.1 IMat (22B parameters) requires approximately 29.7 GB of memory with Q4_K_M quantization.

What is the best quantization for Codestral 22B v0.1 IMat?

The recommended quantization for Codestral 22B v0.1 IMat is Q4_K_M, which balances quality and memory efficiency.

What speed will Codestral 22B v0.1 IMat run at on AMD Instinct MI300A 128GB?

On AMD Instinct MI300A 128GB, Codestral 22B v0.1 IMat achieves approximately 276.5 tokens per second decode speed with a time-to-first-token of 700ms using Q4_K_M quantization.

Can AMD Instinct MI300A 128GB run Codestral 22B v0.1 IMat for coding?

For coding workloads, Codestral 22B v0.1 IMat on AMD Instinct MI300A 128GB receives a C grade with 276.5 tok/s and 626K context.

What context window can Codestral 22B v0.1 IMat use on AMD Instinct MI300A 128GB?

On AMD Instinct MI300A 128GB, Codestral 22B v0.1 IMat can safely use up to 626K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for AMD Instinct MI300A 128GBSee all hardware for Codestral 22B v0.1 IMat
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