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URL: https://willitrunai.com/can-run/sqlcoder-7b-on-h100-nvl-188gb


Can SQLCoder 7B run on H100 NVL 188GB?

YES — Runs Great

A74Great
Estimated from fit model

SQLCoder 7B needs ~26.2 GB VRAM. H100 NVL 188GB has 188.0 GB. With Q4_K_M quantization, expect ~98 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: 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) — 26.2 GB, 98.0 tok/s, Runs well
26.2 GB required188.0 GB available
14% VRAM used

Fit status

Runs well

Decode

98.0 tok/s

TTFT

1976 ms

Safe context

8K

Memory

26.2 GB / 188.0 GB

Memory breakdown

Weights4.3 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom18.8 GB

See how fast it feels

See how fast it feelsSQLCoder 7B on H100 NVL 188GB
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 H100 NVL 188GB (188.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
LowB67
Q3_K_S
3
3.4 GB
LowB67
NVFP4
4

Get started

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

Run

ollama run sqlcoder

Your hardware

More models your H100 NVL 188GB can run

ModelParamsGradeDecodeCapabilities
👁 Mistral
Devstral 2 123B Instruct
123BS91.6 tok/s
👁 Alibaba
Qwen3-Coder 30B A3B Instruct
30.5BS

Frequently asked questions

See all results for H100 NVL 188GBSee all hardware for SQLCoder 7B
3.9 GB
Medium
B67
Q4_K_M
4
4.3 GB
MediumB67
Q5_K_M
5
5.0 GB
HighB67
Q6_K
6
5.7 GB
HighB67
Q8_0
8
7.5 GB
Very HighB67
F16Best for your GPU
16
14.3 GB
MaximumB67
955.4 tok/s
👁 Alibaba
Qwen 3.5 27B
27BS378 tok/s
👁 Alibaba
Qwen 3.6 27B
27BS378 tok/s
👁 Alibaba
Qwen 3.5 122B A10B
122BS254 tok/s