Will It Run AI

Can Mamba Codestral 7B v0.1 run on AMD Instinct MI300X 192GB?

YES — Runs Great

C44Usable
Estimated from fit model

Mamba Codestral 7B v0.1 needs ~25.2 GB VRAM. AMD Instinct MI300X 192GB has 192.0 GB. With Q4_K_M quantization, expect ~98 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) 25.2 GB, 98.0 tok/s, Runs well
25.2 GB required192.0 GB available
13% VRAM used

Fit status

Runs well

Decode

98.0 tok/s

TTFT

1976 ms

Safe context

3.3M

Memory

25.2 GB / 192.0 GB

Memory breakdown

Weights4.3 GB
KV Cache0.8 GB
Runtime0.9 GB
Headroom19.2 GB

See how fast it feels

See how fast it feelsMamba Codestral 7B v0.1 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: 98.0 tok/s decode · 2.0s TTFT (warm) · 245 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 well98.0 tok/s1078 ms3.3M
CodingCRuns well98.0 tok/s1976 ms3.3M
Agentic CodingCRuns well98.0 tok/s2873 ms3.3M
ReasoningCRuns well98.0 tok/s2335 ms3.3M
RAGCRuns well98.0 tok/s3592 ms3.3M

Quantization options

How Mamba Codestral 7B v0.1 (7B params) fits at each quantization level on AMD Instinct MI300X 192GB (192.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowD37
Q3_K_S
3
3.4 GB
LowD37
NVFP4
4
3.9 GB
MediumD37
Q4_K_M
4
4.3 GB
MediumD37
Q5_K_M
5
5.0 GB
HighD37
Q6_K
6
5.7 GB
HighD37
Q8_0
8
7.5 GB
Very HighD37
F16Best for your GPU
16
14.3 GB
MaximumD37

Get started

Copy-paste commands to run Mamba Codestral 7B v0.1 on your machine.

Run

lms load hf-gabriellarson--mamba-codestral-7b-v0-1-gguf && lms server start

Frequently asked questions

Can AMD Instinct MI300X 192GB run Mamba Codestral 7B v0.1?

Yes, AMD Instinct MI300X 192GB can run Mamba Codestral 7B v0.1 with a C grade (Runs well). Expected decode speed: 98.0 tok/s.

How much VRAM does Mamba Codestral 7B v0.1 need?

Mamba Codestral 7B v0.1 (7B parameters) requires approximately 25.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Mamba Codestral 7B v0.1?

The recommended quantization for Mamba Codestral 7B v0.1 is Q4_K_M, which balances quality and memory efficiency.

What speed will Mamba Codestral 7B v0.1 run at on AMD Instinct MI300X 192GB?

On AMD Instinct MI300X 192GB, Mamba Codestral 7B v0.1 achieves approximately 98.0 tokens per second decode speed with a time-to-first-token of 1976ms using Q4_K_M quantization.

Can AMD Instinct MI300X 192GB run Mamba Codestral 7B v0.1 for coding?

For coding workloads, Mamba Codestral 7B v0.1 on AMD Instinct MI300X 192GB receives a C grade with 98.0 tok/s and 3.3M context.

What context window can Mamba Codestral 7B v0.1 use on AMD Instinct MI300X 192GB?

On AMD Instinct MI300X 192GB, Mamba Codestral 7B v0.1 can safely use up to 3.3M tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for AMD Instinct MI300X 192GBSee all hardware for Mamba Codestral 7B v0.1
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