MiniMax Models & API
Compare the MiniMax models available on TokenHub, including MiniMax M3, M2.7, M2.5, M2.1, and M2. Review pricing, context, capabilities, and model IDs, then call MiniMax, MiniMax AI, and MiniMaxAI through one OpenAI-compatible API workflow.
MiniMax Models & API Pricing
Compare current MiniMax API pricing, input and output token costs, context windows, endpoints, and model IDs. The catalog may include MiniMax M3, M2.7, M2.5, M2.1, and M2; availability follows the live TokenHub model list.
Compare input, output, and cache-read prices for the available MiniMax models. Open a model page to confirm the current billing unit and model ID.
Compare context windows, maximum output, reasoning, tool calling, endpoints, and release dates across MiniMax M3, M2.7, M2.5, M2.1, and M2.
Pricing, model availability, context windows, and endpoint support reflect the current TokenHub catalog. Confirm the model detail page before a production release because specifications and availability can change.
Last updated: 2026-08-25Get Started With the MiniMax API
Create a TokenHub API key, copy a published MiniMax model ID, and call it with OpenAI Chat Completions, Responses, or Claude Messages. Existing OpenAI SDK projects can usually switch by changing the API key, Base URL, and model ID.
- 01Create a TokenHub API key
- 02Choose an available MiniMax model
- 03Choose an API protocol
- 04Copy the published MiniMax model ID
- 05Send your first request
Choose an API protocol
import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.TOKENHUB_API_KEY,
baseURL: "https://us-api.tokenhub.com/v1",
})
const result = await client.chat.completions.create({
"model": "MiniMax-M2.5",
"messages": [
{
"role": "user",
"content": "Explain why low latency matters for an AI product in one sentence."
}
]
})
console.log(result.choices[0]?.message?.content)import json
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("TOKENHUB_API_KEY"),
base_url="https://us-api.tokenhub.com/v1",
)
request = json.loads("{\"model\":\"MiniMax-M2.5\",\"messages\":[{\"role\":\"user\",\"content\":\"Explain why low latency matters for an AI product in one sentence.\"}]}")
result = client.chat.completions.create(**request)
print(result.choices[0].message.content)curl 'https://us-api.tokenhub.com/v1/chat/completions' \
-X 'POST' \
-H "Authorization: Bearer $TOKENHUB_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "MiniMax-M2.5",
"messages": [
{
"role": "user",
"content": "Explain why low latency matters for an AI product in one sentence."
}
]
}'const response = await fetch("https://us-api.tokenhub.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.TOKENHUB_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "MiniMax-M2.5",
"messages": [
{
"role": "user",
"content": "Explain why low latency matters for an AI product in one sentence."
}
]
}),
})
const data = await response.json()
console.log(data)import os
import requests
response = requests.request(method="POST", url="https://us-api.tokenhub.com/v1/chat/completions",
headers={
"Authorization": f"Bearer {os.environ['TOKENHUB_API_KEY']}",
"Content-Type": "application/json",
},
json=__import__("json").loads("{\"model\":\"MiniMax-M2.5\",\"messages\":[{\"role\":\"user\",\"content\":\"Explain why low latency matters for an AI product in one sentence.\"}]}"),
)
response.raise_for_status()
print(response.json())import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.TOKENHUB_API_KEY,
baseURL: "https://us-api.tokenhub.com/v1",
})
const result = await client.responses.create({
"model": "MiniMax-M2.5",
"input": "Explain why low latency matters for an AI product in one sentence."
})
console.log(result.output_text)import json
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("TOKENHUB_API_KEY"),
base_url="https://us-api.tokenhub.com/v1",
)
request = json.loads("{\"model\":\"MiniMax-M2.5\",\"input\":\"Explain why low latency matters for an AI product in one sentence.\"}")
result = client.responses.create(**request)
print(result.output_text)curl 'https://us-api.tokenhub.com/v1/responses' \
-X 'POST' \
-H "Authorization: Bearer $TOKENHUB_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "MiniMax-M2.5",
"input": "Explain why low latency matters for an AI product in one sentence."
}'const response = await fetch("https://us-api.tokenhub.com/v1/responses", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.TOKENHUB_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "MiniMax-M2.5",
"input": "Explain why low latency matters for an AI product in one sentence."
}),
})
const data = await response.json()
console.log(data)import os
import requests
response = requests.request(method="POST", url="https://us-api.tokenhub.com/v1/responses",
headers={
"Authorization": f"Bearer {os.environ['TOKENHUB_API_KEY']}",
"Content-Type": "application/json",
},
json=__import__("json").loads("{\"model\":\"MiniMax-M2.5\",\"input\":\"Explain why low latency matters for an AI product in one sentence.\"}"),
)
response.raise_for_status()
print(response.json())curl 'https://us-api.tokenhub.com/v1/messages' \
-X 'POST' \
-H "Authorization: Bearer $TOKENHUB_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "MiniMax-M2.5",
"max_tokens": 1024,
"messages": [
{
"role": "user",
"content": "Explain why low latency matters for an AI product in one sentence."
}
]
}'const response = await fetch("https://us-api.tokenhub.com/v1/messages", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.TOKENHUB_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "MiniMax-M2.5",
"max_tokens": 1024,
"messages": [
{
"role": "user",
"content": "Explain why low latency matters for an AI product in one sentence."
}
]
}),
})
const data = await response.json()
console.log(data)import os
import requests
response = requests.request(method="POST", url="https://us-api.tokenhub.com/v1/messages",
headers={
"Authorization": f"Bearer {os.environ['TOKENHUB_API_KEY']}",
"Content-Type": "application/json",
},
json=__import__("json").loads("{\"model\":\"MiniMax-M2.5\",\"max_tokens\":1024,\"messages\":[{\"role\":\"user\",\"content\":\"Explain why low latency matters for an AI product in one sentence.\"}]}"),
)
response.raise_for_status()
print(response.json())Which MiniMax Model Should You Choose?
Use this MiniMax model selection guide for coding, MiniMax Agent workflows, long-context text, reasoning, and production assistants. Compare price, context, reasoning, tool calling, and endpoint support before shipping.
| API workload | Start with | When it fits | Verify before launch |
|---|---|---|---|
| High-volume MiniMax API calls | MiniMax M2.5 | Fast iteration, chat, extraction, summarization, and batch workloads using MiniMax. | MiniMax API pricing, throughput, and output-token cost |
| MiniMax reasoning and coding | MiniMax M2.5 | Multi-step analysis, code generation, debugging, and agent tasks where answer quality matters. | Reasoning support, tool calling, latency, and total request cost |
| General MiniMax applications | MiniMax M2.5 | Everyday assistants, content generation, information extraction, and product features. | Task accuracy, endpoint support, and production price |
| Long-context MiniMax workloads | MiniMax M3 | Documents, codebases, research, and conversations where input length is the constraint. | Context window, input-token price, maximum output, and streaming |
| Quality-first MiniMax workloads | MiniMax M2.5 | Production outputs where capability matters more than the lowest unit cost. | Task quality, latency, and the price difference versus a faster model |
Choose and Compare MiniMax Models
Use the live catalog to compare MiniMax API price, model specifications, context limits, and supported endpoints.
Integrate MiniMax
Use TokenHub to connect MiniMax to the development tools already in your workflow.
MiniMax API FAQ
What are MiniMax, MiniMax AI, and MiniMaxAI?
MiniMax, MiniMax AI, and MiniMaxAI are names and search terms associated with this model family. TokenHub uses the published provider and model IDs shown in the live catalog.
Which MiniMax models are available on TokenHub?
The live list above shows current availability. Relevant model searches include MiniMax M3, M2.7, M2.5, M2.1, and M2, but only models displayed in the TokenHub catalog can be called through this page.
How do I get a MiniMax API key?
MiniMax API and MiniMax API key searches lead to the same TokenHub workflow: create an API key, select a published MiniMax model ID, and use the TokenHub Base URL in your application.
How is MiniMax API pricing calculated?
Pricing depends on the selected model and billing type. Compare input, output, cache, or per-request prices in the table and confirm the model detail page before production use.
Can I use the OpenAI SDK with MiniMax?
Yes. Use the TokenHub Base URL, API key, and published MiniMax model ID with the OpenAI Python or Node.js SDK. Endpoint support is shown for each model.
Which MiniMax model should I use?
Choose based on the workload: coding, MiniMax Agent workflows, long-context text, reasoning, and production assistants. Compare actual price, context, reasoning, tool calling, and output limits in the live catalog.
Does this page include every MiniMax modality?
MiniMax Audio, MiniMax Speech, and MiniMax Video models use modality-specific pricing and endpoints when available.
Start Building With MiniMax
Choose a MiniMax model, copy its model ID, create a TokenHub API key, and send your first request through one compatible API workflow.