Command R+ 104B needs ~74.2 GB VRAM. NVIDIA A16 64GB has 64.0 GB. With Q4_K_M quantization, expect ~4 tok/s.
Operating mode
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.
Select quantization to explore
10.2 GB over capacity — needs offload or smaller quantization
Fit status
Very compromised (needs ~8.7 GB host RAM)
Decode
4.4 tok/s
TTFT
43874 ms
Safe context
4K
Memory
74.2 GB / 64.0 GB
Offload
10%
It fits through host-memory offload, and offload is the main reason performance drops.
CPU or host-memory offload is active
About 10% of the working set spills out of accelerator memory, which usually hurts latency and sustained decode throughput.
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.
Remove offload with more accelerator memory
Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Increase host RAM if you keep offloading
This setup may need roughly 8.7 GB of extra host RAM just for the offloaded portion, before OS and other tools.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Very compromised (needs ~7.4 GB host RAM) | 4.6 tok/s | 22785 ms | 4K |
| Coding | C | Very compromised (needs ~8.7 GB host RAM) | 4.4 tok/s | 43874 ms | 4K |
| Agentic Coding | F | Too heavy | 4.0 tok/s | 70166 ms | 4K |
| Reasoning | C | Very compromised (needs ~8.7 GB host RAM) | 4.4 tok/s | 51851 ms | 4K |
| RAG | F | Too heavy | 4.0 tok/s | 87707 ms | 4K |
How Command R+ 104B (104B params) fits at each quantization level on NVIDIA A16 64GB (64.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_KBest for your GPU | 2 | 40.6 GB | Low | B65 |
Q3_K_S | 3 | 51.0 GB | Low | F0 |
NVFP4 | 4 | 58.2 GB | Medium | F0 |
Q4_K_M | 4 | 63.4 GB | Medium | F0 |
Q5_K_M | 5 | 74.9 GB | High | F0 |
Q6_K | 6 | 85.3 GB | High | F0 |
Q8_0 | 8 | 111.3 GB | Very High | F0 |
F16 | 16 | 213.2 GB | Maximum | F0 |
Copy-paste commands to run Command R+ 104B on your machine.
Run
ollama run command-r-plusUpgrade options
RTX PRO 6000 Blackwell Workstation Edition 96GBBudget pickRemoves host-memory offload, which is usually the single biggest latency and throughput win.
Raises estimated decode speed by about 486%.
~$9,999 MSRP
RTX PRO 6000 Blackwell Server Edition 96GBBest valueRemoves host-memory offload, which is usually the single biggest latency and throughput win.
Raises estimated decode speed by about 423%.
~$9,999 MSRP
NVIDIA H20 96GBNVIDIA upgradeRemoves host-memory offload, which is usually the single biggest latency and throughput win.
Raises estimated decode speed by about 1161%.
~$12,000 MSRP
Yes, NVIDIA A16 64GB can run Command R+ 104B with a C grade (Very compromised (needs ~8.7 GB host RAM)). Expected decode speed: 4.4 tok/s.
Command R+ 104B (104B parameters) requires approximately 74.2 GB of memory with Q4_K_M quantization.
The recommended quantization for Command R+ 104B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA A16 64GB, Command R+ 104B achieves approximately 4.4 tokens per second decode speed with a time-to-first-token of 43874ms using Q4_K_M quantization.
For coding workloads, Command R+ 104B on NVIDIA A16 64GB receives a C grade with 4.4 tok/s and 4K context.
On NVIDIA A16 64GB, Command R+ 104B can safely use up to 4K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Remove offload with more accelerator memory. Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/command-r-plus-104b-on-a16-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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