FitMyLLM
Cohere/Dense

CohereCommand A 111B

Command A — Cohere's most powerful model. 23 language support, strong agentic capabilities.

chatcodingreasoningmultilingualTool Use
111B
Parameters
250K
Context length
21
Benchmarks
17
Quantizations
50K
HF downloads
Architecture
Dense
Released
2025-03-01
Layers
64
KV Heads
8
Head Dim
128
Family
command

Quantization Options

QuantBitsVRAMQuality
IQ2_XXS2.3833.5 GBlow
IQ2_M2.9341.1 GBlow
Q2_K3.1644.3 GBlow
IQ3_XXS3.2545.6 GBlow
IQ3_XS3.549.1 GBlow
Q3_K_S3.6451.0 GBlow
IQ3_M3.7652.7 GBlow
Q3_K_M456.0 GBlow
Q3_K_L4.360.2 GBmoderate
IQ4_XS4.4662.4 GBmoderate
Q4_K_S4.6765.3 GBmoderate
Q4_K_M4.8968.3 GBgood
Q5_K_S5.5777.8 GBgood
Q5_K_M5.779.6 GBgood
Q6_K6.5691.5 GBexcellent
Q8_08.5118.4 GBlossless
FP1616222.5 GBlossless

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

▸ READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN COMMAND A 111B NOW

Rent on RunPod →Or Vast.ai →

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

Community Ratings

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Benchmarks (21)

Arena Elo1481
MATH-50081.9
IFEval75.4
GPQA Diamond52.7
BBH42.8
MMLU-PRO38.0
IFBench36.5
BigCodeBench33.8
LiveCodeBench28.7
SciCode28.1
MUSR19.8
AA Long Context18.0
τ²-Bench15.2
AA Intelligence13.5
GPQA13.4
AIME13.0
AA Math13.0
MATH12.4
AA Coding9.9
HLE4.6
Terminal-Bench0.8

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run command-a:111b-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
HuggingFaceOllama LibraryGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA RTX PRO 5000 72 GB Blackwell
72 GB VRAM • 1340 GB/s
NVIDIA
$6999
NVIDIA H100 SXM5 80GB
80 GB VRAM • 3350 GB/s
NVIDIA
$25000
NVIDIA H100 PCIe 80GB
80 GB VRAM • 2000 GB/s
NVIDIA
$25000
NVIDIA A100 SXM 80GB
80 GB VRAM • 2039 GB/s
NVIDIA
$10000
NVIDIA A100 PCIe 80GB
80 GB VRAM • 1935 GB/s
NVIDIA
$10000
NVIDIA A100 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$15000
NVIDIA A100 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
$10000
NVIDIA A100X
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H100 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 80 GB
80 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 CNX
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA A800 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
NVIDIA A800 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 SXM5
80 GB VRAM • 3360 GB/s
NVIDIA
NVIDIA RTX 6000D
84 GB VRAM • 1570 GB/s
NVIDIA
$7500
NVIDIA B200
90 GB VRAM • 4100 GB/s
NVIDIA
$30000
NVIDIA H100 NVL 94 GB
94 GB VRAM • 3940 GB/s
NVIDIA
$30000
NVIDIA H100 SXM5 94 GB
94 GB VRAM • 3360 GB/s
NVIDIA
$25000
RTX Pro 6000
96 GB VRAM • 1792 GB/s
NVIDIA
$8565
NVIDIA H100 PCIe 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
Intel Data Center GPU Max 1350
96 GB VRAM • 2460 GB/s
INTEL
NVIDIA RTX PRO 6000 Blackwell Server
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
NVIDIA RTX PRO 6000 Blackwell
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
AMD Instinct MI300A
120 GB VRAM • 5300 GB/s
AMD
$12000
Apple M4 Max (128GB)
128 GB VRAM • 546 GB/s
APPLE
$3999
AMD Instinct MI250X
128 GB VRAM • 3277 GB/s
AMD
$10000
Apple M1 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$4999
Apple M2 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$3999

Find the best GPU for Command A 111B

Build Hardware for Command A 111B

Model Card

View on HuggingFace

Command A — Cohere's most powerful model. 23 language support, strong agentic capabilities.

▸ SPEC SHEET

Command A 111B — 111B Dense.

▸ SPECIFICATIONS
PARAMETERS
111B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
250K tokens
CAPABILITIES
chat, coding, reasoning, multilingual
RELEASE DATE
2025-03-01
PROVIDER
Cohere
FAMILY
command
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ2_XXS2.3833.5 GB65%
IQ2_M2.9341.1 GB75%
Q2_K3.1644.3 GB78%
IQ3_XXS3.2545.6 GB82%
IQ3_XS3.549.1 GB84%
Q3_K_S3.6451.0 GB85%
IQ3_M3.7652.7 GB86%
Q3_K_M456.0 GB88%
Q3_K_L4.360.2 GB90%
IQ4_XS4.4662.4 GB92%
Q4_K_S4.6765.3 GB93%
Q4_K_M4.8968.3 GB94%
Q5_K_S5.5777.8 GB96%
Q5_K_M5.779.6 GB96%
Q6_K6.5691.5 GB97%
Q8_08.5118.4 GB100%
FP1616222.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO38.0
MATH12.4
IFEval75.4
BBH42.8
GPQA13.4
MUSR19.8
BigCodeBench33.8
Arena Elo1481.0
GPQA Diamond52.7
LiveCodeBench28.7
AIME13.0
MATH-50081.9
HLE4.6
AA Intelligence13.5
AA Coding9.9
AA Math13.0
aa_ifbench36.5
aa_terminal_bench0.8
aa_tau215.2
aa_scicode28.1
aa_lcr18.0
§ 02RUN COMMAND

Run Command A 111B locally with Ollama — needs 68.3 GB VRAM at Q4_K_M:

$ollama run command-a:111b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
NVIDIA RTX PRO 5000 72 GB Blackwell
72 GB · 1340 GB/s
NVIDIA H100 SXM5 80GB
80 GB · 3350 GB/s
NVIDIA H100 PCIe 80GB
80 GB · 2000 GB/s
NVIDIA A100 SXM 80GB
80 GB · 2039 GB/s
NVIDIA A100 PCIe 80GB
80 GB · 1935 GB/s
NVIDIA A100 SXM4 80 GB
80 GB · 2040 GB/s
NVIDIA A100 PCIe 80 GB
80 GB · 1940 GB/s
NVIDIA A100X
80 GB · 2040 GB/s
NVIDIA H100 PCIe 80 GB
80 GB · 2040 GB/s
NVIDIA H100 SXM5 80 GB
80 GB · 3360 GB/s
NVIDIA H100 CNX
80 GB · 2040 GB/s
NVIDIA A800 PCIe 80 GB
80 GB · 1940 GB/s
NVIDIA A800 SXM4 80 GB
80 GB · 2040 GB/s
NVIDIA H800 PCIe 80 GB
80 GB · 2040 GB/s
NVIDIA H800 SXM5
80 GB · 3360 GB/s