Will It Run AI

Can Leanstral 119B A6B run on NVIDIA H20 96GB?

YES — With NVFP4

S89Excellent
Estimated from fit model

Leanstral 119B A6B needs ~87.4 GB VRAM. NVIDIA H20 96GB has 96.0 GB. With NVFP4 quantization, expect ~81 tok/s.

Runtime: vLLMCapacity: TightBandwidth: HighStack: OptimizedBottleneck: 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.

Leanstral 119B A6B at Q4_K_M needs 93.4 GB — too much for NVIDIA H20 96GB (96.0 GB). Runs at NVFP4 (87.4 GB) with medium quality. 3 quantization levels fit.
Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) 93.4 GB, exceeds 96.0 GB available
93.4 GB required96.0 GB available
97% VRAM used

Fit status

Too heavy

Decode

71.1 tok/s

TTFT

2724 ms

Safe context

21K

Memory

93.4 GB / 96.0 GB

Memory breakdown

Weights72.6 GB
KV Cache8.8 GB
Runtime2.4 GB
Headroom9.6 GB

See how fast it feels

With memory offload — actual speed may be lower
See how fast it feelsLeanstral 119B A6B 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: 71.1 tok/s decode · 2.7s TTFT (warm) · 178 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 fit71.1 tok/s1486 ms21K
CodingFToo heavy71.1 tok/s2724 ms21K
Agentic CodingFToo heavy54.7 tok/s5149 ms21K
ReasoningFToo heavy71.1 tok/s3220 ms21K
RAGFToo heavy54.7 tok/s6436 ms21K

Quantization options

How Leanstral 119B A6B (119B params) fits at each quantization level on NVIDIA H20 96GB (96.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
46.4 GB
LowA83
Q3_K_S
3
58.3 GB
LowA84
NVFP4
4
66.6 GB
MediumA84
Q4_K_MBest for your GPU
4
72.6 GB
MediumA84
Q5_K_M
5
85.7 GB
HighF0
Q6_K
6
97.6 GB
HighF0
Q8_0
8
127.3 GB
Very HighF0
F16
16
244.0 GB
MaximumF0

Get started

Copy-paste commands to run Leanstral 119B A6B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \ --hf-repo "mistralai/Leanstral-2603" \ --hf-file "Leanstral-2603-Q4_K_M.gguf" \ -c 4096 -ngl 99

升级选项

能流畅运行 Leanstral 119B A6B 的硬件

Frequently asked questions

Can NVIDIA H20 96GB run Leanstral 119B A6B?

Yes, NVIDIA H20 96GB can run Leanstral 119B A6B at NVFP4 quantization (Tight fit). The recommended Q4_K_M requires 93.4 GB which exceeds available memory, but at NVFP4 it needs only 87.4 GB. Expected decode speed: 81.3 tok/s.

How much VRAM does Leanstral 119B A6B need?

Leanstral 119B A6B (119B parameters) requires approximately 93.4 GB at Q4_K_M quantization. On NVIDIA H20 96GB, it fits at NVFP4 using 87.4 GB.

What is the best quantization for Leanstral 119B A6B?

The recommended quantization is Q4_K_M, but on NVIDIA H20 96GB the best fitting quantization is NVFP4, which uses 87.4 GB.

What speed will Leanstral 119B A6B run at on NVIDIA H20 96GB?

On NVIDIA H20 96GB, Leanstral 119B A6B achieves approximately 81.3 tokens per second decode speed with a time-to-first-token of 2382ms using NVFP4 quantization.

Can NVIDIA H20 96GB run Leanstral 119B A6B for coding?

For coding workloads, Leanstral 119B A6B on NVIDIA H20 96GB receives a F grade with 71.1 tok/s and 21K context.

What context window can Leanstral 119B A6B use on NVIDIA H20 96GB?

On NVIDIA H20 96GB, Leanstral 119B A6B can safely use up to 32K tokens of context at NVFP4 quantization. The model's official context limit is 256K, but available memory constrains the safe maximum.

See all results for NVIDIA H20 96GBSee all hardware for Leanstral 119B A6B
Embed this result

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/leanstral-119b-a6b-on-h20-96gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: