Use the MiniMax API via RunAPI with a model skill, unified auth, and pay-as-you-go pricing.
# Base URL
https://runapi.ai
# Endpoints
POST /v1/chat/completions
POST /v1/responses
POST /v1/messages
POST /v1beta/models/{model}:generateContent
POST /v1beta/models/{model}:streamGenerateContent
curl https://runapi.ai/v1/chat/completions \
-H "Authorization: Bearer $RUNAPI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "MiniMax-M3",
"messages": [
{
"role": "user",
"content": "Given this API spec, generate a typed client, write integration tests against a mock server, and iterate until they pass."
}
]
}'from openai import OpenAI
client = OpenAI(
base_url="https://runapi.ai/v1",
api_key="your-runapi-key"
)
response = client.chat.completions.create(
model="MiniMax-M3",
messages=[{"role": "user", "content": "Given this API spec, generate a typed client, write integration tests against a mock server, and iterate until they pass."}]
)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://runapi.ai/v1",
apiKey: "your-runapi-key"
});
const response = await client.chat.completions.create({
model: "MiniMax-M3",
messages: [{ role: "user", content: "Given this API spec, generate a typed client, write integration tests against a mock server, and iterate until they pass." }]
});MiniMax's M-series are sparse Mixture-of-Experts text models built for cost-efficient coding. M2 through M2.7 (230B total / ~10B active, 256 experts) offer 200K context with progressively stronger agentic capabilities — M2.7 reaches 56.2% on SWE-bench Pro. MiniMax-M3 uses a larger, different architecture to restore 1M context with a new Sparse Attention design, scoring 80.5% on SWE-bench Verified and 59.0% on SWE-bench Pro. Highspeed variants run the same weights at ~100 tokens/sec for latency-sensitive work. All are available through RunAPI with one key and per-token billing.
| Endpoint | Protocol |
|---|---|
POST /v1/chat/completions | OpenAI compatible |
POST /v1/responses | OpenAI Responses |
POST /v1/messages | Anthropic compatible |
POST /v1beta/models/{model}:generateContent | Gemini generateContent |
POST /v1beta/models/{model}:streamGenerateContent | Gemini streamGenerateContent |
| Variant | Billing | Pricing | |
|---|---|---|---|
| MiniMax-M2 | 1K tokens | Input $0.19 / 1M tokens | Output $0.73 / 1M tokens | View → |
| MiniMax-M2.1 | 1K tokens | Input $0.19 / 1M tokens | Output $0.73 / 1M tokens | View → |
| MiniMax-M2.5 | 1K tokens | Input $0.19 / 1M tokens | Output $0.73 / 1M tokens | View → |
| MiniMax-M2.5-highspeed | 1K tokens | Input $0.37 / 1M tokens | Output $1.46 / 1M tokens | View → |
| MiniMax-M2.7 | 1K tokens | Input $0.19 / 1M tokens | Output $0.73 / 1M tokens | View → |
| MiniMax-M2.7-highspeed | 1K tokens | Input $0.37 / 1M tokens | Output $1.46 / 1M tokens | View → |
| MiniMax-M3 | 1K tokens | Input $0.18-$0.36 / 1M tokens | Output $0.72-$1.44 / 1M tokens | View → |
| Endpoint | Resolution | Duration | Price | |
|---|---|---|---|---|
| chat_completion | — | — | Input $0.19 / 1M tokens | Output $0.73 / 1M tokens |
Prices shown for MiniMax-M2. Other variants retain their own endpoint pricing.
Sign up and generate an API key from the dashboard.
Choose the version that best matches your quality and cost requirements.
Submit your prompt and parameters to the model's documented endpoint.
Poll the task or set a webhook, then download the completed output.
MiniMax M-series text models are sparse MoE LLMs with 200K–1M context, delivering frontier coding scores at a fraction of the cost of dense models. Through RunAPI they share a single API key with pay-as-you-go token billing, callable from the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages surfaces. These are MiniMax's text models, distinct from MiniMax Hailuo video generation.
A single RunAPI API key unlocks the whole model catalog across all providers. No separate accounts to create, no API keys to rotate per integration, and no credential management overhead. Add a new model to your app by changing one parameter.
Per-call pricing in USD, billed monthly into a single invoice. No subscription tiers, no minimum spend, and failed generations are never charged. The pricing page and check_pricing API show exact costs before you commit to a model.
Typed schemas, parameter constraints, and setup notes are packaged in the model skill so your implementation starts from the right contract. The skill loads into Claude Code, Codex, Gemini CLI, Cursor, and VS Code — your agent knows the correct request shape before you write a line of code.
No. These are MiniMax's text language models for coding and chat; Hailuo is MiniMax's separate video generation line.
MiniMax-M3 is the strongest — 1M context, 80.5% SWE-bench Verified, and the first open-weight model to combine frontier coding with million-token context. M2.7 is the best 200K-context option. Highspeed variants (M2.5 and M2.7) run the same weights at ~100 tokens/sec for lower latency at higher token cost.
Use the OpenAI SDK (Chat Completions or Responses) or the Anthropic Messages SDK against RunAPI with the MiniMax model id; the proxy adapts the protocol.
Per token at RunAPI's published input and output rates for each model, pay-as-you-go. Highspeed variants are billed at their own published rates for the same output quality at higher throughput.
Pick the cheapest variant that meets your quality bar. Most teams start on the fast variant and graduate to pro for production.
Creating an account and API key is free. API calls use prepaid, pay-as-you-go billing; add funds before making requests.