VOOZH about

URL: https://willitrunai.com/can-run/command-r-plus-104b-on-a40-48gb

⇱

Can Command R+ 104B run on NVIDIA A40 48GB?

YES — With Q2_K

B64Good
○Estimated from fit model

Command R+ 104B needs ~49.7 GB VRAM. NVIDIA A40 48GB has 48.0 GB. With Q2_K quantization, expect ~9 tok/s.

Runtime: llama.cppCapacity: OffloadBandwidth: MediumStack: 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.

Command R+ 104B at Q4_K_M needs 72.6 GB — too much for NVIDIA A40 48GB (48.0 GB). Runs at Q2_K (49.7 GB) with low quality.
Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 72.6 GB, exceeds 48.0 GB available
72.6 GB required48.0 GB available
151% VRAM needed

24.6 GB over capacity — needs offload or smaller quantization

Fit status

Too heavy

Decode

2.9 tok/s

TTFT

66192 ms

Safe context

4K

Memory

72.6 GB / 48.0 GB

Offload

30%

Memory breakdown

Weights63.4 GB
KV Cache3.4 GB
Runtime0.9 GB
Headroom4.8 GB

See how fast it feels

With memory offload — actual speed may be lower
See how fast it feelsCommand R+ 104B on NVIDIA A40 48GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step. Given information: - Speed = 60 mph (miles per hour) - Time = 2.5 hours Formula: Distance = Speed x Time Calculation: Distance = 60 mph x 2.5 h = 150 miles The train travels 150 miles. Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time. Breakdown: - First half: 1.25 hours at 60 mph = 75 miles - Stop: 20 minutes (no distance) - Second half: 1.25 hours at 60 mph = 75 miles Total distance: 150 miles (same) Total time: 2.5 h + 0.33 h = 2.83 hours Average speed: 150 / 2.83 = 53 mph The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 2.9 tok/s decode · 66.2s TTFT (warm) · 7 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Very little memory headroom

You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.

Best improvement path

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatFToo heavy2.8 tok/s37342 ms4K
CodingFToo heavy2.7 tok/s71984 ms4K
Agentic CodingFToo heavy2.4 tok/s115356 ms4K
ReasoningFToo heavy2.7 tok/s85071 ms4K
RAGFToo heavy2.4 tok/s144195 ms4K

Quantization options

How Command R+ 104B (104B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
40.6 GB
LowF0
Q3_K_S
3
51.0 GB
LowF0
NVFP4
4

Get started

Copy-paste commands to run Command R+ 104B on your machine.

Run

ollama run command-r-plus

Upgrade options

Hardware that runs Command R+ 104B well

👁 NVIDIA
NVIDIA A16 64GBBest value
64 GB VRAM (+16)
C
Makes the model fit on the accelerator instead of staying completely out of reach.4.4 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Raises estimated decode speed by about 52%.

~$6,500 MSRP

👁 NVIDIA
RTX PRO 6000 Blackwell Workstation Edition 96GBBudget pick
96 GB VRAM (+48)1792 GB/s (+1096)
A
Makes the model fit on the accelerator instead of staying completely out of reach.25.8 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Removes host-memory offload, which is usually the single biggest latency and throughput win.

~$9,999 MSRP

👁 NVIDIA
RTX PRO 6000 Blackwell Server Edition 96GBNVIDIA upgrade
96 GB VRAM (+48)1597 GB/s (+901)
B
Makes the model fit on the accelerator instead of staying completely out of reach.23 tok/s decode

Makes the model fit on the accelerator instead of staying completely out of reach.

Removes host-memory offload, which is usually the single biggest latency and throughput win.

~$9,999 MSRP

Frequently asked questions

See all results for NVIDIA A40 48GBSee all hardware for Command R+ 104B
58.2 GB
Medium
F0
Q4_K_M
4
63.4 GB
MediumF0
Q5_K_M
5
74.9 GB
HighF0
Q6_K
6
85.3 GB
HighF0
Q8_0
8
111.3 GB
Very HighF0
F16
16
213.2 GB
MaximumF0

Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.