Will It Run AI

Can Command A 111B run on NVIDIA H20 96GB?

YES — Tight Fit

S92Excellent
Estimated from fit model

Command A 111B needs ~82.1 GB VRAM. NVIDIA H20 96GB has 96.0 GB. With Q4_K_M quantization, expect ~48 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: 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) 82.1 GB, 52.2 tok/s, Tight fit
82.1 GB required96.0 GB available
86% VRAM used

Fit status

Tight fit

Decode

52.2 tok/s

TTFT

3706 ms

Safe context

73K

Memory

82.1 GB / 96.0 GB

Memory breakdown

Weights67.7 GB
KV Cache3.9 GB
Runtime0.9 GB
Headroom9.6 GB

See how fast it feels

See how fast it feelsCommand A 111B on NVIDIA H20 96GB
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: 52.2 tok/s decode · 3.7s TTFT (warm) · 131 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
ChatSTight fit47.9 tok/s2207 ms73K
CodingSTight fit47.9 tok/s4046 ms73K
Agentic CodingSTight fit47.9 tok/s5885 ms73K
ReasoningSTight fit47.9 tok/s4781 ms73K
RAGSTight fit47.9 tok/s7356 ms73K

Quantization options

How Command A 111B (111B params) fits at each quantization level on NVIDIA H20 96GB (96.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
43.3 GB
LowS87
Q3_K_S
3
54.4 GB
LowS88
NVFP4
4
62.2 GB
MediumS88
Q4_K_MBest for your GPU
4
67.7 GB
MediumS88
Q5_K_M
5
79.9 GB
HighF0
Q6_K
6
91.0 GB
HighF0
Q8_0
8
118.8 GB
Very HighF0
F16
16
227.6 GB
MaximumF0

Get started

Copy-paste commands to run Command A 111B on your machine.

Run

ollama run command-a

Your hardware

More models your NVIDIA H20 96GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BS47 tok/s
AlibabaQwen 3.5 122B A10B122BS130.3 tok/s
MistralMistral Small 4 119B119BS141.2 tok/s
OpenAIGPT-OSS 120B117BS49.4 tok/s

Frequently asked questions

Can NVIDIA H20 96GB run Command A 111B?

Yes, NVIDIA H20 96GB can run Command A 111B with a S grade (Tight fit). Expected decode speed: 47.9 tok/s.

How much VRAM does Command A 111B need?

Command A 111B (111B parameters) requires approximately 82.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Command A 111B?

The recommended quantization for Command A 111B is Q4_K_M, which balances quality and memory efficiency.

What speed will Command A 111B run at on NVIDIA H20 96GB?

On NVIDIA H20 96GB, Command A 111B achieves approximately 47.9 tokens per second decode speed with a time-to-first-token of 4046ms using Q4_K_M quantization.

Can NVIDIA H20 96GB run Command A 111B for coding?

For coding workloads, Command A 111B on NVIDIA H20 96GB receives a S grade with 47.9 tok/s and 73K context.

What context window can Command A 111B use on NVIDIA H20 96GB?

On NVIDIA H20 96GB, Command A 111B can safely use up to 73K tokens of context. The model's official context limit is 262K, but available memory constrains the safe maximum.

See all results for NVIDIA H20 96GBSee all hardware for Command A 111B
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