FitMyLLM
Cohere/Dense

CohereCommand-R7B

Cohere's compact RAG-optimized model with strong retrieval capabilities.

chatreasoningTool Use
8.03B
Parameters
128K
Context length
7
Benchmarks
6
Quantizations
40K
HF downloads
Architecture
Dense
Released
2024-12-13
Layers
32
KV Heads
8
Head Dim
128
Family
command

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q4_K_M4.89
6.9 GB
5.4 + 1.5 KV
good
Q5_K_S5.57
7.6 GB
6.1 + 1.5 KV
good
Q5_K_M5.7
7.7 GB
6.2 + 1.5 KV
good
Q6_K6.56
8.6 GB
7.1 + 1.5 KV
excellent
Q8_08.5
10.5 GB
9.0 + 1.5 KV
lossless
FP1616
18.0 GB
16.5 + 1.5 KV
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

Deploying for a team or in production? Size GPUs, cost & scaling in Enterprise →
READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN COMMAND-R7B NOW

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

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Benchmarks (7)

IFEval71.0
HumanEval54.0
MMLU-PRO38.0
BBH36.0
MATH29.9
MUSR10.2
GPQA7.8

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run command-r7b:7b-12-2024-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA Tesla C2070
6 GB VRAM • 143 GB/s
NVIDIA
NVIDIA Tesla C2075
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla C2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla M2070
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2070-Q
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2075
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla X2070
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla X2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla K20X
6 GB VRAM • 250 GB/s
NVIDIA
NVIDIA Tesla K20Xm
6 GB VRAM • 250 GB/s
NVIDIA

Find the best GPU for Command-R7B

Build Hardware for Command-R7B

Cohere's compact RAG-optimized model with strong retrieval capabilities.

▸ SPEC SHEET

Command-R7B8.03B Dense.

▸ SPECIFICATIONS
PARAMETERS
8.03B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
128K tokens
CAPABILITIES
chat, reasoning
RELEASE DATE
2024-12-13
PROVIDER
Cohere
FAMILY
command
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.895.4 GB94%
Q5_K_S5.576.1 GB96%
Q5_K_M5.76.2 GB96%
Q6_K6.567.1 GB97%
Q8_08.59.0 GB100%
FP161616.5 GB100%
§ 01BENCHMARK SCORES
HumanEval54.0
MMLU-PRO38.0
MATH29.9
IFEval71.0
BBH36.0
GPQA7.8
MUSR10.2
§ 02RUN COMMAND

Run Command-R7B locally with Ollama — needs 5.4 GB VRAM at Q4_K_M:

$ollama run command-r7b:7b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M