Command R+ (104B) — VRAM, Speed & Local Setup

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 4 kwietnia 2024

Model library → Command R Family → Command R+ (104B)

Cohere's flagship model for complex enterprise RAG. Handles multi-hop retrieval, grounded citations, and complex tool orchestration. Outperforms GPT-4 Turbo on RAG benchmarks.

Command R+ (104B) needs about 64 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters104 Billion
Context window128,000
ArchitectureDense
ProviderCohere
LicenceCC-BY-NC
Specified atQ4_K_M
System RAM128 GB
Record updated2024-04-04

Licence

CC-BY-NC-4.0 — research / non-commercial only. Research / non-commercial only — this licence does NOT permit shipping a commercial product.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB), at 8K context. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

QuantWeightsVRAM neededEst. speedFit on 24 GB
Q2_K34.2 GB37.1 GB~3 tok/s (est.)Offloads to system RAM (slow)
Q3_K_M44.3 GB47.3 GB~2 tok/s (est.)Offloads to system RAM (slow)
Q4_K_M62.8 GB65.7 GB—Won't fit
Q5_K_M73.7 GB76.7 GB—Won't fit
Q6_K85.3 GB88.2 GB—Won't fit
Q8_0110.5 GB113.4 GB—Won't fit
F16208.0 GB210.9 GB—Won't fit

Want the memory numbers alone, at every quantization level and your own context length? Use the Command R+ (104B) VRAM calculator.

Buy This HardwareApple MacBook Pro M5 Pro — 64 GB VRAM · 30 W board powerDeploy in the Cloud NowNVIDIA A100 80GB on RunPod — from $1.39/hr · rate checked 2026-07

or compare on Vast.ai from $0.77/hr (typical low · varies)

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Recommended GPU

The cheapest catalogued GPU that runs Command R+ (104B) is the Apple M5 Pro (64 GB).

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.
Apple MacBook Pro M5 Pro
64 GB VRAM · 30 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

How to Run Command R+ (104B)

Install Ollama, then run:

ollama run command-r-plus

Weights on Hugging Face: CohereForAI/c4ai-command-r-plus.

Best for: enterprise rag, agent, complex retrieval.

Can I Run Command R+ (104B) on My GPU?

Other Command R Family Sizes

Command R+ (104B) — Frequently Asked Questions

How much VRAM does Command R+ (104B) need?
About 64 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does Command R+ (104B) run on an RTX 4090 (24 GB)?
No. Command R+ (104B) needs about 64 GB at Q4_K_M, more than a single RTX 4090's 24 GB. It needs a larger card, several GPUs, or Apple Silicon with enough unified memory — or it runs with part of the weights offloaded to system RAM, which is much slower.
How do I run Command R+ (104B) locally?
Install Ollama and run `ollama run command-r-plus`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does Command R Family come in?
Command R (35B) (22 GB), Command R+ (104B) (64 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

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