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URL: https://willitrunai.com/can-run/sqlcoder-7b-on-instinct-mi300a-128gb


Can SQLCoder 7B run on AMD Instinct MI300A 128GB?

YES — Runs Great

A75Great
Estimated from fit model

SQLCoder 7B needs ~19.9 GB VRAM. AMD Instinct MI300A 128GB has 128.0 GB. With Q4_K_M quantization, expect ~98 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: StandardBottleneck: Balanced
Share:

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) — 19.9 GB, 98.0 tok/s, Runs well
19.9 GB required128.0 GB available
16% VRAM used

Fit status

Runs well

Decode

98.0 tok/s

TTFT

1976 ms

Safe context

8K

Memory

19.9 GB / 128.0 GB

Memory breakdown

Weights4.3 GB
KV Cache2.0 GB
Runtime0.9 GB
Headroom12.8 GB

See how fast it feels

See how fast it feelsSQLCoder 7B 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: 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
ChatARuns well98.0 tok/s1078 ms8K
CodingARuns well98.0 tok/s1976 ms8K
Agentic CodingARuns well98.0 tok/s2873 ms8K
ReasoningARuns well98.0 tok/s2335 ms8K
RAGARuns well98.0 tok/s3592 ms8K

Quantization options

How SQLCoder 7B (7B params) fits at each quantization level on AMD Instinct MI300A 128GB (128.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowB68
Q3_K_S
3
3.4 GB
LowB68
NVFP4
4

Get started

Copy-paste commands to run SQLCoder 7B on your machine.

Run

ollama run sqlcoder

Your hardware

More models your AMD Instinct MI300A 128GB can run

ModelParamsGradeDecodeCapabilities
👁 Mistral
Devstral 2 123B Instruct
123BS53.8 tok/s
👁 Alibaba
Qwen3-Coder 30B A3B Instruct
30.5BS

Frequently asked questions

See all results for AMD Instinct MI300A 128GBSee all hardware for SQLCoder 7B
3.9 GB
Medium
B68
Q4_K_M
4
4.3 GB
MediumB68
Q5_K_M
5
5.0 GB
HighB68
Q6_K
6
5.7 GB
HighB68
Q8_0
8
7.5 GB
Very HighB68
F16Best for your GPU
16
14.3 GB
MaximumB68
561 tok/s
👁 Alibaba
Qwen 3.5 27B
27BS243.3 tok/s
👁 Alibaba
Qwen 3.6 27B
27BS151.7 tok/s
👁 Alibaba
Qwen 3.5 122B A10B
122BS149.2 tok/s