C4ai Command R Plus 08 2024 — Hardware Requirements & GPU Compatibility
Chat
C4AI Command R+ 08-2024 is Cohere Labs' 103.8-billion-parameter flagship chat model, an August 2024 refresh of the original Command R+ built for retrieval-augmented generation with citations, single-step tool use (function calling), and multi-step agentic tool use across sequential actions. Like the smaller Command R 08-2024 released alongside it, it is an auto-regressive transformer using grouped-query attention, trained and evaluated across a wide multilingual set including English, French, Spanish, German, Japanese, Korean, Arabic, and Simplified Chinese. Cohere positions it as an open-weights research release with more advanced reasoning, summarization, and question-answering capability than the smaller Command R model. At 103.8 billion parameters, it needs a multi-GPU workstation or server to run, even once quantized. Context length is 128,000 tokens. It is released under a Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license plus Cohere's Acceptable Use Policy, restricting the model to non-commercial use. It was published in August 2024.
165 downloads
301 likesSpecifications
- Publisher
- Cohere
- Family
- Command R
- Parameters
- 103.8B
- Release Date
- 2024-08-21
- License
- CC BY-NC 4.0
Get Started
HuggingFace
How Much VRAM Does C4ai Command R Plus 08 2024 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 48.5 GB | — | 44.12 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 50.0 GB | — | 45.42 GB | 3-bit small quantization |
| Q3_K_Mest. | 3.90 | 55.7 GB | — | 50.61 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 68.5 GB | — | 62.29 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 81.4 GB | — | 73.97 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 94.2 GB | — | 85.64 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 114.2 GB | — | 103.81 GB | 8-bit quantization, near-lossless |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run C4ai Command R Plus 08 2024?
Q4_K_M · 68.5 GBC4ai Command R Plus 08 2024 (Q4_K_M) requires 68.5 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 90+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run C4ai Command R Plus 08 2024?
Q4_K_M · 68.5 GB19 devices with unified memory can run C4ai Command R Plus 08 2024, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 96GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download C4ai Command R Plus 08 2024
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Benchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does C4ai Command R Plus 08 2024 need?
C4ai Command R Plus 08 2024 requires 68.5 GB of VRAM at Q4_K_M, or 228.4 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 103.8B × 4.8 bits ÷ 8 = 62.3 GB
KV Cache + Overhead ≈ 6.2 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M68.5 GB- Can NVIDIA GeForce RTX 5090 run C4ai Command R Plus 08 2024?
No — C4ai Command R Plus 08 2024 requires at least 47.1 GB at IQ3_XS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for C4ai Command R Plus 08 2024?
For C4ai Command R Plus 08 2024, Q4_K_M (68.5 GB) offers the best balance of quality and VRAM usage. Q5_K_M (81.4 GB) provides better quality if you have the VRAM. The smallest option is IQ3_XS at 47.1 GB.
VRAM requirement by quantization
IQ3_XS47.1 GBQ3_K_S50.0 GBQ3_K_M55.7 GBQ4_K_M ★68.5 GBQ6_K94.2 GBBF16228.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run C4ai Command R Plus 08 2024 on a Mac?
C4ai Command R Plus 08 2024 requires at least 47.1 GB at IQ3_XS, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run C4ai Command R Plus 08 2024 locally?
Yes — C4ai Command R Plus 08 2024 can run locally on consumer hardware. At Q4_K_M quantization it needs 68.5 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is C4ai Command R Plus 08 2024?
At Q4_K_M, C4ai Command R Plus 08 2024 can reach ~70 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 68.5 × 0.65 = ~76 tok/s
Estimated speed at Q4_K_M (68.5 GB)
~76 tok/s~76 tok/s~70 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of C4ai Command R Plus 08 2024?
At Q4_K_M, the download is about 62.29 GB. The full-precision BF16 version is 207.62 GB. The smallest option (IQ3_XS) is 42.82 GB.
- Which GPUs can run C4ai Command R Plus 08 2024?
No single consumer GPU has enough VRAM to run C4ai Command R Plus 08 2024 at Q4_K_M (68.5 GB). Multi-GPU or professional hardware is required.
- Which devices can run C4ai Command R Plus 08 2024?
19 devices with unified memory can run C4ai Command R Plus 08 2024 at Q4_K_M (68.5 GB), including ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.