Everything you need to know about Cohere's command

Cohere has entered the competitive race of launching LLM with its last offer: Command A. Its previous model, Command R+, was launched in August 2024, followed by the R7B Command in December 2024. Now, with Command A, Cohere has made a strong return, introducing a generative language model of adapted art status for business use cases. Optimized for high performance with minimal hardware demands, command A provides a profitable and efficient solution for companies. It joins the set of coherent models, recognized for its scalability and robust performance in a wide range of applications. Let's learn more about this in this article!

What is the Cofre A command?

Command A is a powerful 111b parameter model with a 256K context length, which allows it to handle much longer documents compared to most of the main models. It stands out in areas such as tools, generation generation of generation (RAG), multilingual agents and use cases. This model is designed to be highly efficient, which requires only two GPUs (A100S/H100), which is significantly lower than other comparable models

New features:

• Web search
• Python interpreter
• API integration
• Database interaction
• Generation of generation recovery (rag)
• Agents and complex reasoning
• Multilingual support (23 languages)
• Business Degree Security

Performance and reference points

COHERE COMMAND A is a large -language model (LLM) that stands out, especially for companies. Here is why it is special:

Great performance, less power

The command A offers strong results using less computer power. It has 111 billion parameters and a context length of 256k, but only needs two GPUs (such as A100 or H100) to execute. Compare that with Deepseek V3, which needs eight GPUs for a context length of 128k. This makes the command a powerful but affordable for companies.

Super fast

It is 150% faster than the previous model of Cohere, Command R+ (launched in August 2024). You can handle 156 tokens per second, beating models such as Openi and Deepseek V3 GPT-4o in speed and efficiency.

Built for business

Command a brightness in the tasks that companies need:

• Generation generation of the generation (rag): Use external data well, which makes it excellent for things such as extracting financial information or answering long file questions. The A and GPT-4O command were compared in business RAG tasks. The trained scorers qualified them blindly on fluidity, precision and utility.

Use of tools and agents: It works with tools such as search engines or API and run fast agents for difficult thought and research tasks.

Multilingual: It admits 23 languages ​​(as English, Spanish, Arabic and Japanese), so it works for users around the world and can also be translated. When it has been commissioned with Depseek V3 in extensive users of human evaluation, they firmly preferred an Over Deepseek-V3 in most languages ​​in a variety of business use cases.

Command at vs GPT 4 (Arabaica)

Affordable

How to access the A command?

Cohing Platform

• Create an account on the COHER platform if you still don't have one.
• Select the “Chat With Chere” option

Hugged face

The command A is also available for the use of research on the hugged face. You can access it through the following steps:

Model page: Visit the C4AI command a model page on the hugged face.

Facility: Install the transformers Library of the origin repository that includes the necessary changes for this model.

pip install transformers

Example of use

from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "CohereForAI/c4ai-command-a-03-2025"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

# Format message with the c4ai-command-a-03-2025 chat template
messages = ({"role": "user", "content": "Hello, how are you?"})
input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")

gen_tokens = model.generate(
    input_ids,
    max_new_tokens=100,
    do_sample=True,
    temperature=0.3,
)

gen_text = tokenizer.decode(gen_tokens(0))
print(gen_text)

• Try it: You can also try the A command in the hug space of hugs lodged before downloading the weights.

Note: The command will soon be available in the main cloud suppliers. Be attentive to coherent ads for updates

Let's try to command a

I will try some of the characteristics offered by the command to:

Task 1: Web search

Immediate: “Trace the average rental price of 1 room in February 2025 for the 5 most expensive cities in India.“

Production:

Observation:

Command has done decently but could not find rental prices for New Delhi and Chennai, probably because it only verified 10 websites. For web searches, google, perplexity or kimi k1.5 are better options

Also read: OpenAi vs Google: Who does better research?

Task 2: Research

Immediate: “Trace the five main companies in the solar panel industry for revenue last year. “

Production:

Observation:

The research feature is average. It is fine for fast responses, but for detailed reports or in -depth analysis, use OpenAi's deep research option.

Task 3: Learn a new topic

Immediate: “Draw without (x) from -2pi to 2pi, using a passage size of 0.05, and explain mathematics as if it were five.“

Production:

The sinusoidal function, or without (x), is a mathematical function that describes a soft wave pattern. Imagine that you are in a swing, and when you swing forward and backward, your height goes up and down in a soft and repeated pattern. That is similar to how the sinusoidal function looks!

The sinusoidal function takes an entrance value, x, and gives it a value between -1 and 1. when traces without (x) in a graph, you get a wavy line that goes up and down, crossing the XA axis regular intervals.

In the previous graph, the x axis represents the input values ​​of x, ranging from -2π to 2π. The Y axis represents the corresponding sinus values. The size of the passage of 0.05 means that the graph is calculated and draws at intervals of 0.05 along the x axis, which gives it a soft and detailed representation of the sinusoidal wave.

Think about it how to draw a wavy line in a piece of paper, but instead of drawing it by hand, it is using a rule to ensure that each point is exactly 0.05 units away. The result is a beautiful and symmetrical wave that is repeated as it goes from left to right.

Observation:

The exit effectively meets both requirements: plans correctly without (x) from -2π to 2π using the size of 0.05 steps with the appropriate code, while explaining the concept with a friendly language for children and an identifiable swing analogy. Technical implementation and simplified explanation work without problems to meet the dual objectives of the notice.

Conclusion

The A command is definitely better than the previous coherent models, offering options that each other LLM is offering today. Is it the best model that exists? Not precisely. Try yours and let me know your experience in the comments section below!

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