Command A
Cohere · dense · 111B parameters · 256,000 context
Parameters
111B
Context Window
250K tokens
Architecture
Dense
Best GPU
H20
Cheapest API
$10.00/M
Quality Score
81/100
Intelligence Brief
Command A is a 111B parameter DENSE model from Cohere, featuring Grouped Query Attention (GQA) with 72 layers and 10,240 hidden dimensions. With a 256,000 token context window, it supports tools, structured output, code, math, multilingual, reasoning. On standardized benchmarks, it achieves MMLU 83, HumanEval 55, GSM8K 88. The most cost-effective API deployment is via cohere at $10.00/M output tokens. For self-hosted inference, H20 delivers optimal throughput at $3758/month.
Architecture Details
Memory Requirements
BF16 Weights
222.0 GB
FP8 Weights
111.0 GB
INT4 Weights
55.5 GB
GPU Compatibility Matrix
Command A is compatible with 21% of GPU configurations across 41 GPUs at 3 precision levels.
GPU Recommendations
BF16 · 4 GPUs · tensorrt-llm
90/100
score
Throughput
280.0 tok/s
Latency (ITL)
3.6ms
Est. TTFT
1ms
Cost/Month
$3758
Cost/M Tokens
$5.11
BF16 · 1 GPU · tensorrt-llm
88/100
score
Throughput
280.0 tok/s
Latency (ITL)
3.6ms
Est. TTFT
1ms
Cost/Month
$9965
Cost/M Tokens
$13.54
BF16 · 2 GPUs · tensorrt-llm
83/100
score
Throughput
280.0 tok/s
Latency (ITL)
3.6ms
Est. TTFT
1ms
Cost/Month
$8522
Cost/M Tokens
$11.58
Deployment Options
API Deployment
cohere
$10.00/M
output tokens
Single GPU
B200 NVL (pair)
$9965/mo
Min VRAM: 111 GB
Multi-GPU
H20 x4
280.0 tok/s
TP· $3758/mo
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| cohere | $2.50 | $10.00 | Cheapest |
Cost Analysis
| Provider | Input $/M | Output $/M | ~Monthly Cost |
|---|---|---|---|
| cohereBest Value | $2.50 | $10.00 | $63 |
Cost per 1,000 Requests
Short (500 tok)
$3.25
via cohere
Medium (2K tok)
$13.00
via cohere
Long (8K tok)
$40.00
via cohere
Performance Estimates
Throughput by GPU
VRAM Breakdown (H20, BF16)
Quality Benchmarks
Capabilities
Features
Supported Frameworks
Supported Precisions
Where to Deploy Command A
Self-Hosted Infrastructure
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Frequently Asked Questions
How much VRAM does Command A need for inference?
Command A requires approximately 222.0 GB of VRAM at BF16 precision, 111.0 GB at FP8, or 55.5 GB at INT4 quantization. Additional VRAM is needed for KV-cache (184320 bytes per token) and activations (~3.50 GB).
What is the best GPU for Command A?
The top recommended GPU for Command A is the H20 (x4) using BF16 precision. It achieves approximately 280.0 tokens/sec at an estimated cost of $3758/month ($5.11/M tokens). Score: 90/100.
How much does Command A inference cost?
Command A API inference starts from $2.50/M input tokens and $10.00/M output tokens. Self-hosted inference costs depend on your GPU configuration — use our ROI calculator for a detailed breakdown.