MiniMax M2.1 long-context model
MiniMax M2.1 stands out as a premier long-context model within the MiniMax family, engineered for complex reasoning tasks requiring extensive information retention. With a massive 1,000,000 token context window, this model excels at processing entire codebases, legal documents, or lengthy technical manuals without losing coherence. Running at FP16 precision, it delivers high-fidelity outputs suitable for production-grade applications where accuracy is paramount. As a proprietary offering on LLM Resayil, it ensures enterprise-grade reliability while maintaining strict data handling standards required for sensitive development workflows.
Developers should integrate MiniMax M2.1 when their applications demand deep contextual understanding beyond standard limits. Although it carries a 2.5x credit multiplier relative to the base rate, the trade-off provides unparalleled retrieval accuracy and reduced hallucination rates over long sequences. Accessible from the starter tier, this model lowers the barrier for building sophisticated agents capable of multi-step analysis. Choose MiniMax M2.1 to empower your chat interfaces with the ability to synthesize vast amounts of data instantly, ensuring your users receive precise, context-aware responses every time.
from openai import OpenAI
client = OpenAI(
base_url="https://llmapi.resayil.io/v1/",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="minimax-m2.1",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)import anthropic
client = anthropic.Anthropic(
base_url="https://llmapi.resayil.io/v1",
api_key="YOUR_API_KEY"
)
message = client.messages.create(
model="minimax-m2.1",
max_tokens=1024,
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(message.content[0].text)const response = await fetch(
"https://llmapi.resayil.io/v1/chat/completions",
{
method: "POST",
headers: {
"Content-Type": "application/json",
"Authorization": "Bearer YOUR_API_KEY"
},
body: JSON.stringify({
model: "minimax-m2.1",
messages: [
{ role: "user", content: "Hello!" }
]
})
}
);
const data = await response.json();
console.log(data.choices[0].message.content);curl https://llmapi.resayil.io/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "minimax-m2.1",
"messages": [
{"role": "user", "content": "Hello!"}
]
}'