willitrun·ai

Can Granite Code 20B run on RTX PRO 6000 Blackwell Workstation Edition 96GB?

YES — Runs Great

A77Great
Estimated from fit model

Granite Code 20B needs ~26.2 GB VRAM. RTX PRO 6000 Blackwell Workstation Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~133 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: 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) 26.2 GB, 133.3 tok/s, Runs well
26.2 GB required96.0 GB available
27% VRAM used

Fit status

Runs well

Decode

133.3 tok/s

TTFT

1453 ms

Safe context

8K

Memory

26.2 GB / 96.0 GB

Memory breakdown

Weights12.2 GB
KV Cache3.2 GB
Runtime1.2 GB
Headroom9.6 GB

See how fast it feels

See how fast it feelsGranite Code 20B on RTX PRO 6000 Blackwell Workstation Edition 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: 133.3 tok/s decode · 1.5s TTFT (warm) · 333 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 well133.3 tok/s792 ms8K
CodingARuns well133.3 tok/s1453 ms8K
Agentic CodingARuns well133.3 tok/s2113 ms8K
ReasoningARuns well133.3 tok/s1717 ms8K
RAGARuns well133.3 tok/s2642 ms8K

Inference speed

Granite Code 20B inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for Granite Code 20B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~106 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.

GPU / MacMemoryQuantSpeed (tok/s)Fits?
NVIDIARTX 5090 32GB
32 GBQ4_K_M106.3Fits
NVIDIARTX 4090 24GB
24 GBQ4_K_M67.8Fits
RX 7900 XTX 24GB
24 GBQ4_K_M61.2Fits
NVIDIARTX 3090 24GB
24 GBQ4_K_M58.0Fits
Mac Studio M3 Ultra 256GB
256 GBQ4_K_M49.3Fits
Mac Studio M2 Ultra 128GB
128 GBQ4_K_M41.1Fits
Mac Studio M1 Ultra 128GB
128 GBQ4_K_M39.0Fits
MacBook Pro M4 Max 128GB
128 GBQ4_K_M38.4Fits
MacBook Pro M4 Max 64GB
64 GBQ4_K_M38.4Fits
NVIDIARTX 4080 Super 16GB
16 GBQ4_K_M31.0Heavy offload
MacBook Pro M4 Pro 48GB
48 GBQ4_K_M24.2Fits
MacBook Pro M3 Max 64GB
64 GBQ4_K_M21.2Fits
MacBook Pro M1 Max 64GB
64 GBQ4_K_M19.5Fits
NVIDIARTX 4070 12GB
12 GBQ4_K_M11.0Too big
NVIDIARTX 3060 12GB
12 GBQ4_K_M6.9Too big
NVIDIARTX 4060 8GB
8 GBQ4_K_M2.6Too big

Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.

Quantization options

How Granite Code 20B (20B params) fits at each quantization level on RTX PRO 6000 Blackwell Workstation Edition 96GB (96.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
7.8 GB
LowB69
Q3_K_S
3
9.8 GB
LowB69
NVFP4
4
11.2 GB
MediumB69
Q4_K_M
4
12.2 GB
MediumB69
Q5_K_M
5
14.4 GB
HighB70
Q6_K
6
16.4 GB
HighB70
Q8_0
8
21.4 GB
Very HighA70
F16Best for your GPU
16
41.0 GB
MaximumA74

Get started

Copy-paste commands to run Granite Code 20B on your machine.

Run

ollama run granite-code:20b

Your hardware

More models your RTX PRO 6000 Blackwell Workstation Edition 96GB can run

ModelParamsGradeDecodeCapabilities
MistralDevstral 2 123B Instruct123BS21.8 tok/s
AlibabaQwen3-Coder 30B A3B Instruct30.5BS227.6 tok/s
AlibabaQwen 3.5 27B27BS98.7 tok/s
AlibabaQwen 3.6 27B27BS99 tok/s
AlibabaQwen 3.5 122B A10B122BS60.5 tok/s

Frequently asked questions

Can RTX PRO 6000 Blackwell Workstation Edition 96GB run Granite Code 20B?

Yes, RTX PRO 6000 Blackwell Workstation Edition 96GB can run Granite Code 20B with a A grade (Runs well). Expected decode speed: 133.3 tok/s.

How much VRAM does Granite Code 20B need?

Granite Code 20B (20B parameters) requires approximately 26.2 GB of memory with Q4_K_M quantization.

What is the best quantization for Granite Code 20B?

The recommended quantization for Granite Code 20B is Q4_K_M, which balances quality and memory efficiency.

What speed will Granite Code 20B run at on RTX PRO 6000 Blackwell Workstation Edition 96GB?

On RTX PRO 6000 Blackwell Workstation Edition 96GB, Granite Code 20B achieves approximately 133.3 tokens per second decode speed with a time-to-first-token of 1453ms using Q4_K_M quantization.

Can RTX PRO 6000 Blackwell Workstation Edition 96GB run Granite Code 20B for coding?

For coding workloads, Granite Code 20B on RTX PRO 6000 Blackwell Workstation Edition 96GB receives a A grade with 133.3 tok/s and 8K context.

What context window can Granite Code 20B use on RTX PRO 6000 Blackwell Workstation Edition 96GB?

On RTX PRO 6000 Blackwell Workstation Edition 96GB, Granite Code 20B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.

See all results for RTX PRO 6000 Blackwell Workstation Edition 96GBSee all hardware for Granite Code 20B
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