C4ai Command A 03 2025 — Hardware Requirements & GPU Compatibility
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C4ai Command A 03 2025 is a 111.1B-parameter open language model from Cohere. At Q2_K it needs about 51.92 GB of VRAM — see which GPUs and Macs can run it below.
2.8K downloads
392 likesSpecifications
- Publisher
- Cohere
- Parameters
- 111.1B
- Release Date
- 2025-10-30
- License
- CC BY-NC 4.0
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HuggingFace
How Much VRAM Does C4ai Command A 03 2025 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 51.9 GB | — | 47.20 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 53.5 GB | — | 48.59 GB | 3-bit small quantization |
Which GPUs Can Run C4ai Command A 03 2025?
Q2_K · 51.9 GBC4ai Command A 03 2025 (Q2_K) requires 51.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 68+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run C4ai Command A 03 2025?
Q2_K · 51.9 GB8 devices with unified memory can run C4ai Command A 03 2025, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (64 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightBenchmarks
View all 1 →Related Models
Frequently Asked Questions
- How much VRAM does C4ai Command A 03 2025 need?
C4ai Command A 03 2025 requires 51.9 GB of VRAM at Q2_K, or 53.5 GB at Q3_K_S.
VRAM = Weights + KV Cache + Overhead
Weights = 111.1B × 3.4 bits ÷ 8 = 47.2 GB
KV Cache + Overhead ≈ 4.7 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q2_K51.9 GB- Can NVIDIA GeForce RTX 5090 run C4ai Command A 03 2025?
No — C4ai Command A 03 2025 requires at least 51.9 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for C4ai Command A 03 2025?
For C4ai Command A 03 2025, Q3_K_S (53.5 GB) offers the best balance of quality and VRAM usage. The smallest option is Q2_K at 51.9 GB.
VRAM requirement by quantization
Q2_K51.9 GBQ3_K_S ★53.5 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run C4ai Command A 03 2025 on a Mac?
C4ai Command A 03 2025 requires at least 51.9 GB at Q2_K, 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 A 03 2025 locally?
Yes — C4ai Command A 03 2025 can run locally on consumer hardware. At Q2_K quantization it needs 51.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is C4ai Command A 03 2025?
At Q2_K, C4ai Command A 03 2025 can reach ~56 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 51.9 × 0.55 = ~56 tok/s
Estimated speed at Q2_K (51.9 GB)
~56 tok/s~42 tok/s~35 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 A 03 2025?
At Q2_K, the download is about 47.20 GB. The full-precision Q3_K_S version is 48.59 GB.
- Which GPUs can run C4ai Command A 03 2025?
No single consumer GPU has enough VRAM to run C4ai Command A 03 2025 at Q2_K (51.9 GB). Multi-GPU or professional hardware is required.
- Which devices can run C4ai Command A 03 2025?
8 devices with unified memory can run C4ai Command A 03 2025 at Q2_K (51.9 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), Mac Studio M4 Max (64 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.