Command R 7B
Cohere · dense · 7B parameters · 131,072 context
Parameters
7B
Context Window
128K tokens
Architecture
Dense
Best GPU
A10G
Cheapest API
$0.15/M
Quality Score
68/100
Intelligence Brief
Command R 7B is a 7B parameter DENSE model from Cohere, featuring Grouped Query Attention (GQA) with 32 layers and 4,096 hidden dimensions. With a 131,072 token context window, it supports tools, structured output, code, multilingual. On standardized benchmarks, it achieves MMLU 73, HumanEval 42, GSM8K 75. The most cost-effective API deployment is via cohere at $0.15/M output tokens. For self-hosted inference, A10G delivers optimal throughput at $285/month.
Architecture Details
Memory Requirements
BF16 Weights
14.0 GB
FP8 Weights
7.0 GB
INT4 Weights
3.5 GB
GPU Compatibility Matrix
Command R 7B is compatible with 95% of GPU configurations across 41 GPUs at 3 precision levels.
GPU Recommendations
BF16 · 1 GPU · vllm
100/100
score
Throughput
231.4 tok/s
Latency (ITL)
4.3ms
Est. TTFT
1ms
Cost/Month
$285
Cost/M Tokens
$0.47
BF16 · 1 GPU · vllm
100/100
score
Throughput
359.9 tok/s
Latency (ITL)
2.8ms
Est. TTFT
0ms
Cost/Month
$332
Cost/M Tokens
$0.35
BF16 · 1 GPU · vllm
100/100
score
Throughput
388.8 tok/s
Latency (ITL)
2.6ms
Est. TTFT
0ms
Cost/Month
$370
Cost/M Tokens
$0.36
Deployment Options
API Deployment
cohere
$0.15/M
output tokens
Single GPU
A10G
$285/mo
Min VRAM: 7 GB
Multi-GPU
RTX 3080 x2
452.6 tok/s
TP· $266/mo
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| cohere | $0.07 | $0.15 | Cheapest |
Cost Analysis
| Provider | Input $/M | Output $/M | ~Monthly Cost |
|---|---|---|---|
| cohereBest Value | $0.07 | $0.15 | $1 |
Cost per 1,000 Requests
Short (500 tok)
$0.07
via cohere
Medium (2K tok)
$0.27
via cohere
Long (8K tok)
$0.90
via cohere
Performance Estimates
Throughput by GPU
VRAM Breakdown (A10G, BF16)
Precision Impact
bf16
14.0 GB
weights/GPU
~231.4 tok/s
fp8
7.0 GB
weights/GPU
int4
3.5 GB
weights/GPU
Quality Benchmarks
Capabilities
Features
Supported Frameworks
Supported Precisions
Where to Deploy Command R 7B
Self-Hosted Infrastructure
Similar Models
OLMo 2 7B
7B params · dense
Quality: 50
Falcon 7B
7B params · dense
Quality: 37
from $0.15/M
Zephyr 7B
7B params · dense
Quality: 50
Vicuna 7B
7B params · dense
Quality: 50
Code Llama 7B
7B params · dense
Quality: 39
from $0.20/M
Frequently Asked Questions
How much VRAM does Command R 7B need for inference?
Command R 7B requires approximately 14.0 GB of VRAM at BF16 precision, 7.0 GB at FP8, or 3.5 GB at INT4 quantization. Additional VRAM is needed for KV-cache (131072 bytes per token) and activations (~0.80 GB).
What is the best GPU for Command R 7B?
The top recommended GPU for Command R 7B is the A10G using BF16 precision. It achieves approximately 231.4 tokens/sec at an estimated cost of $285/month ($0.47/M tokens). Score: 100/100.
How much does Command R 7B inference cost?
Command R 7B API inference starts from $0.07/M input tokens and $0.15/M output tokens. Self-hosted inference costs depend on your GPU configuration — use our ROI calculator for a detailed breakdown.