MiniMax M2.1 Lightning
MiniMax M2.1 Lightning is the throughput-optimized variant of MiniMax-M2.1. It supports a context window of 204.8K tokens and a max output of 131.1K tokens per request.
View API reference- Input and output price
- Input $0.30, Output $2.40, Per 1M tokens
- 24h uptime
- Loading AI Gateway uptime
import { streamText } from 'ai'
const result = streamText({ model: 'minimax/minimax-m2.1-lightning', prompt: 'Why is the sky blue?'})Copy link to headingPlayground
Try out MiniMax M2.1 Lightning by MiniMax. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.
MiniMax M2.1 Lightning
MiniMax M2.1 Lightning
Copy link to headingProviders
Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.
Copy link to headingUptime24 hours
Direct request success rate on AI Gateway and per-provider. Visit the docs for more info.
Copy link to headingThroughput24 hours
P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the docs for more info.
Copy link to headingLatency24 hours
P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the docs for more info.
Getting started
Call MiniMax M2.1 Lightning through AI Gateway with the AI SDK generateText and streamText functions, or through the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs by changing the base URL. AI Gateway authenticates the request and routes it to an available provider.
Install the AI SDK (pnpm add ai dotenv), create an API key from the API Keys page, and set it as AI_GATEWAY_API_KEY in your environment. Full setup is covered in the text generation quickstart.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'minimax/minimax-m2.1-lightning', prompt: 'Why is the sky blue?', });
console.log(result.text);}
main().catch(console.error);Top-level parameters
The same MiniMax M2.1 Lightning request in each API format AI Gateway supports.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'minimax/minimax-m2.1-lightning', system: 'You are a concise technical assistant.', prompt: 'Summarize the tradeoffs between static generation and SSR.', maxOutputTokens: 1024, });
console.log(result.text);}
main().catch(console.error);Standard parameters like prompt, messages, temperature, and tools work as documented in the AI SDK docs. These are the parameters with model-specific behavior.
| Parameter | Type | Required | Description |
|---|---|---|---|
model | string | Yes | Model ID in the form creator/model, e.g. minimax/minimax-m2.1-lightning. AI Gateway routes the request to an available provider. |
maxOutputTokens | number | No | Hard cap on generated tokens. MiniMax M2.1 Lightning supports up to 131,072 output tokens. Reasoning tokens count toward this limit. |
reasoning | 'provider-default' | 'none' | 'minimal' | 'low' | 'medium' | 'high' | 'xhigh' | No | Provider-agnostic reasoning effort, available in AI SDK 7 or later. Maps to the provider’s native reasoning configuration; reasoning settings under providerOptions take precedence when both are set. See the Reasoning section below. |
providerOptions | Record<string, JSONValue> | No | AI Gateway routing options under gateway, plus any provider-native options under the provider’s own namespace — see the table below. |
Input limits
| Input | Formats | Sources | Max count | Max size | Limits |
|---|---|---|---|---|---|
| Text | — | — | — | — | Prompt and response share the 205K-token context window |
Provider options
Set AI Gateway routing options under providerOptions.gateway. For provider-specific options, pass them under the provider’s namespace as documented by the AI SDK.
Learn more in the AI SDK provider docs.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'minimax/minimax-m2.1-lightning', prompt: 'Why is the sky blue?', providerOptions: { gateway: { only: ['minimax'], }, }, });
console.log(result.text);}
main().catch(console.error);These AI Gateway routing options apply to every model. Provider-specific options pass through under the provider’s own namespace (for example providerOptions.anthropic) exactly as documented by the AI SDK.
| Parameter | Type | Required | Description |
|---|---|---|---|
providerOptions.gateway.only | string[] | No | Restrict routing to these provider slugs. Requests fail over only within the listed providers. |
providerOptions.gateway.order | string[] | No | Preferred provider order. Listed providers are tried first; unlisted providers remain available as fallbacks. |
providerOptions.gateway.sort | 'cost' | 'ttft' | 'tps' | No | Rank candidate providers by price, time to first token, or tokens per second instead of the default routing order. |
providerOptions.gateway.zeroDataRetention | boolean | No | Route only to providers with a zero-data-retention policy for this model. |
Routing across providers
AI Gateway serves the same model through multiple providers and fails over automatically. order expresses a preference while keeping every provider eligible; only is a hard allowlist — if none of the listed providers are available the request fails instead of falling back.
Options under a provider's own namespace (for example providerOptions.anthropic) are forwarded to that provider with the request. Providers ignore option namespaces that don't apply to them, so it is safe to set provider options alongside gateway routing options.
Reasoning
AI Gateway bridges reasoning across every API format. The AI SDK exposes a provider-agnostic top-level reasoning level (none, minimal, low, medium, high, or xhigh); the Chat Completions and Responses formats take the same effort under reasoning.effort; and the Anthropic Messages format uses a native thinking token budget. Whichever you send, the gateway maps it to the target model’s native configuration, converting between effort levels and token budgets as needed. Reasoning-related settings under providerOptions take full precedence over the top-level reasoning value and are never merged. Reasoning tokens typically count toward your output-token usage, though how they’re reported and billed varies by provider.
Learn more in the AI Gateway reasoning guide.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'minimax/minimax-m2.1-lightning', prompt: 'Explain the Monty Hall problem step by step.', reasoning: 'high', });
console.log(result.text);}
main().catch(console.error);Tool calling
Expose tools the model can call. Define each tool’s inputs with a Zod schema.
import { generateText, tool } from 'ai';import { z } from 'zod';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'minimax/minimax-m2.1-lightning', prompt: 'What is the weather in San Francisco?', tools: { getWeather: tool({ description: 'Get the current weather for a location', inputSchema: z.object({ location: z.string() }), execute: async ({ location }) => ({ location, temperatureC: 18 }), }), }, });
console.log(result.text);}
main().catch(console.error);Copy link to headingMore models by MiniMax
| Model |
|---|
| 1M | 0.7 s | 158 tps | $0.26/M | $1.02/M | Read$0.06/M | — | +2 |   +2 | 05/31/2026 | |||||
| 205K | 1.1 s | 54 tps | $0.30/M+1 more | $1.20/M+1 more | Read$0.06/M Write$0.38/M | — |  | 03/18/2026 | ||||||
| 205K | 0.9 s | 65 tps | $0.60/M | $2.40/M | Read$0.06/M Write$0.38/M | — | | 03/18/2026 | ||||||
| 1M | 0.6 s | 78 tps | $0.27/M+1 more | $0.95/M+1 more | Read$0.03/M Write$0.38/M | — |   +1 | 02/12/2026 | ||||||
| 205K | 0.5 s | 140 tps | $0.30/M | $1.20/M | Read$0.03/M Write$0.38/M | — | | 12/23/2025 | ||||||
| 205K | 0.8 s | 82 tps | $0.30/M | $1.20/M | Read$0.03/M Write$0.38/M | — | | 10/27/2025 |
Copy link to headingAbout MiniMax M2.1 Lightning
MiniMax M2.1 Lightning shipped alongside M2.1 as its speed-optimized companion. The Lightning variant delivers faster inference while maintaining identical outputs to standard M2.1. You don't trade quality for throughput.
The model supports the same programming languages as M2.1: Go, C++, JavaScript, C#, TypeScript, Rust, Java, Kotlin, and Objective-C. It also carries the same Interleaved Thinking capability and agentic tool-use support that define the 2.1 generation.
Automatic prompt caching is built in with no manual configuration. This further reduces effective latency for repeated or structurally similar prompts. MiniMax M2.1 Lightning suits developer tools, IDE assistants, and any application where users expect near-instantaneous code suggestions.
Copy link to headingWhat To Consider When Choosing a Provider
- Configuration: For streaming use cases where time-to-first-token matters most, MiniMax M2.1 Lightning's throughput advantage translates directly into a more responsive end-user experience.
- Zero Data Retention: Zero Data Retention is offered on a per-provider and model basis. See the documentation for details.
- Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.
Copy link to headingWhen to Use MiniMax M2.1 Lightning
Best for
- Interactive developer tools: IDE plugins where response latency is user-visible
- Real-time code completion: Inline suggestion features in web or IDE applications where latency is visible
- High-throughput batch jobs: Faster tokens-per-second reduces job duration
- Streaming user experiences: Applications that need low time-to-first-token
- Drop-in speed upgrade: Teams already on M2.1 who want faster inference
Consider alternatives when
- Minimize cost: Throughput is not a constraint, so use standard M2.1
- Architectural planning needed: Your tasks require the planning capabilities introduced in M2.5
- Vision input required: M2.1 Lightning is text-only, so use a multimodal model when your workload includes image inputs
Copy link to headingConclusion
MiniMax M2.1 Lightning resolves the typical quality-vs-speed tradeoff by matching M2.1's output while running faster. It's a straightforward upgrade for any latency-sensitive application already using the 2.1 generation. Built-in prompt caching amplifies the speed benefit for repetitive context patterns.
Copy link to headingFrequently Asked Questions
Does MiniMax M2.1 Lightning produce different outputs than standard M2.1?
No. MiniMax M2.1 Lightning produces identical outputs to standard M2.1. Only inference speed differs.
How much faster is MiniMax M2.1 Lightning compared to M2.1?
Lightning is the throughput-optimized variant, built to outperform M2 on output speed. See live metrics on this page for current AI Gateway measurements.
Does automatic prompt caching apply to all requests?
Yes. Prompt caching applies automatically with no manual configuration. It reduces latency for prompts with repeated context.
Is MiniMax M2.1 Lightning more expensive than M2.1?
Yes, typically. Expect about $0.3 per million input tokens and $2.4 per million output tokens for this variant (compare to standard M2.1 on the same page).
What programming languages does MiniMax M2.1 Lightning support?
The same languages as M2.1: Go, C++, JavaScript, C#, TypeScript, Rust, Java, Kotlin, and Objective-C.
Can I use MiniMax M2.1 Lightning for agentic workflows with tool calls?
Yes. MiniMax M2.1 Lightning retains all of M2.1's agentic capabilities, including tool use, multi-step reasoning, and Interleaved Thinking.
How do I switch from M2.1 to MiniMax M2.1 Lightning in the AI SDK?
Change the model identifier to
minimax/minimax-m2.1-lightning. No other code changes are needed.