✅ RUNS NATIVE FP16 & ALL QUANTIZATIONS
Cohere Command-A 111B on 8x NVIDIA H100 80GB (640GB) (640GB VRAM)
In 4-bit Q4_K_M, Cohere Command-A 111B uses only 71.99 GB of your 640 GB VRAM (11% utilization) at ~30.9 tokens/sec. In full 16-bit precision, it requires 231.33 GB.
🎛️ Interactive VRAM & KV-Cache Tuner
📊 Real-Time Memory Footprint
71.99 GB / 640 GB
🟦 Weights (69.31 GB)
🟪 KV Cache (2 GB)
🟨 Activation Buffer (0.67 GB)
Total Required VRAM71.99 GB
Available Hardware VRAM640 GB (8x NVIDIA H100 80GB (640GB))
VRAM Headroom / Overflow568.01 GB
Estimated Generation Speed~30.9 tokens/sec
Architecture & AttentionDense-GQA (64L, 8 KV heads)
🚀 Ready-to-Run Launch Command
ollama run command-a:111b # Or with llama.cpp server (8K context, Flash Attention): llama-server -hf CohereForAI/c4ai-command-a-03-2025-GGUF -c 8192 -ngl 99 -fa
CLOUD GPU ALTERNATIVE
Need 71.99 GB+ VRAM to run Cohere Command-A 111B?
Recommended cloud setup for 4-bit: NVIDIA A100 / H100 (80GB) (or 231.33 GB for full FP16). Spin up a pre-configured vLLM / Ollama instance in 60 seconds:
| Provider | Best For | RTX 4090 (24GB) | A100 (80GB) | H100 (80GB) | Bonus / Trial | Action |
|---|---|---|---|---|---|---|
| RunPod | 1-Click vLLM / Ollama Pods | $0.44 / hr | $1.39 / hr | $2.39 / hr | Instant PyTorch / vLLM Pods + Serverless GPU | Deploy on RunPod → |
| Vast.ai | Cheapest Spot GPU Market | $0.29 / hr | $0.95 / hr | $1.79 / hr | Save 50–70% on RTX 4090 / 5090 / A100 rentals | Check Spot GPUs → |
| Vultr Cloud GPU | Enterprise SLA & Bare Metal | — | $1.79 / hr | $2.69 / hr | $300 Free Credit for New Users | Claim $300 Credit → |
| DigitalOcean GPU Droplets | Managed H100 Droplets | — | — | $2.99 / hr | $200 Free Trial (60 Days) | Get $200 Free → |
All Quantization Formats: Cohere Command-A 111B on 8x NVIDIA H100 80GB (640GB)
| Quantization Format | Bits/Weight | Weights VRAM | KV Cache (8K) | Total VRAM | Fits on 1x 8x NVIDIA H100 80GB (640GB) (640GB)? | Est. Speed | GPUs Needed |
|---|---|---|---|---|---|---|---|
| FP16 / BF16 (Unquantized) | 16 bpw | 228.66 GB | 2 GB | 231.33 GB | Yes (36%) | ~9.4 tok/s | 1x 8x NVIDIA H100 80GB (640GB) |
| FP8 (W8A8 / E4M3) | 8.5 bpw | 121.48 GB | 2 GB | 124.15 GB | Yes (19%) | ~17.6 tok/s | 1x 8x NVIDIA H100 80GB (640GB) |
| GGUF Q8_0 (8-bit) | 8.5 bpw | 121.48 GB | 2 GB | 124.15 GB | Yes (19%) | ~17.6 tok/s | 1x 8x NVIDIA H100 80GB (640GB) |
| GGUF Q6_K (6-bit) | 6.56 bpw | 93.75 GB | 2 GB | 96.42 GB | Yes (15%) | ~22.8 tok/s | 1x 8x NVIDIA H100 80GB (640GB) |
| GGUF Q5_K_M (5-bit) | 5.69 bpw | 81.32 GB | 2 GB | 83.99 GB | Yes (13%) | ~26.3 tok/s | 1x 8x NVIDIA H100 80GB (640GB) |
| GGUF Q4_K_M / AWQ (4-bit) | 4.85 bpw | 69.31 GB | 2 GB | 71.99 GB | Yes (11%) | ~30.9 tok/s | 1x 8x NVIDIA H100 80GB (640GB) |
| GGUF IQ4_XS (4.25 bpw) | 4.25 bpw | 60.74 GB | 2 GB | 63.41 GB | Yes (10%) | ~35.2 tok/s | 1x 8x NVIDIA H100 80GB (640GB) |
| GGUF Q3_K_M (3-bit) | 3.91 bpw | 55.88 GB | 2 GB | 58.55 GB | Yes (9%) | ~38.3 tok/s | 1x 8x NVIDIA H100 80GB (640GB) |
Frequently Asked Questions (Cohere Command-A 111B + 8x NVIDIA H100 80GB (640GB))
Can 8x NVIDIA H100 80GB (640GB) (640GB) run Cohere Command-A 111B locally?
Yes — 8x NVIDIA H100 80GB (640GB) (640GB) easily runs Cohere Command-A 111B even in full FP16. In 4-bit Q4_K_M, Cohere Command-A 111B uses only 71.99 GB of your 640 GB VRAM (11% utilization) at ~30.9 tokens/sec. In full 16-bit precision, it requires 231.33 GB.
How is KV Cache calculated for Cohere Command-A 111B?
Cohere Command-A 111B uses Dense-GQA with 64 transformer layers, 96 attention heads, and 8 KV heads (head dimension 128). At 8,192 tokens in FP16, KV cache consumes 2 GB. Enabling 8-bit KV cache (-ctk q8_0 -ctv q8_0 in llama.cpp or --kv-cache-dtype fp8 in vLLM) cuts this in half to 1.00 GB.
Compare Cohere Command-A 111B on Other GPUs
Cohere Command-A 111B on NVIDIA RTX 5090 (32GB)Cohere Command-A 111B on NVIDIA RTX 4090 (24GB)Cohere Command-A 111B on NVIDIA RTX 5080 (16GB)Cohere Command-A 111B on NVIDIA RTX 4080 Super (16GB)Cohere Command-A 111B on NVIDIA RTX 4070 Ti Super (16GB)Cohere Command-A 111B on NVIDIA RTX 3090 (24GB)Cohere Command-A 111B on NVIDIA RTX 4060 Ti 16GB (16GB)Cohere Command-A 111B on NVIDIA RTX 3060 12GB (12GB)Cohere Command-A 111B on NVIDIA RTX 6000 Ada (48GB)Cohere Command-A 111B on NVIDIA RTX A6000 (48GB)
Other Models on 8x NVIDIA H100 80GB (640GB) (640GB)
DeepSeek-R1 671B (MoE) on 8x NVIDIA H100 80GB (640GB)DeepSeek-V3 671B (MoE) on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Llama-70B on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Qwen-32B on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Qwen-14B on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Llama-8B on 8x NVIDIA H100 80GB (640GB)DeepSeek-R1-Distill-Qwen-7B on 8x NVIDIA H100 80GB (640GB)Qwen3-235B-A22B (MoE) on 8x NVIDIA H100 80GB (640GB)Qwen3-30B-A3B (MoE) on 8x NVIDIA H100 80GB (640GB)Qwen3-32B on 8x NVIDIA H100 80GB (640GB)