Does MiniMax Text 01 support streaming?

Yes—at least one listed provider advertises streaming.

What is the context length for MiniMax Text 01?

Reported context for MiniMax Text 01 is 1M tokens. Always verify the active provider row if multiple providers are listed.

When should I choose MiniMax Text 01?

You need a general-purpose text model for assistants, agents, or content workflows — especially when you specifically need MiniMax Text 01.

Where is the canonical page for MiniMax Text 01?

https://llmapi.ai/models/minimax-text-01/

Which providers serve MiniMax Text 01?

LLM.API currently lists: minimax. Availability can vary by region and account.

How do I call MiniMax Text 01 via API?

Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "minimax-text-01" and your LLM.API key. See the code snippet on this page.

What modalities does MiniMax Text 01 support?

MiniMax Text 01 accepts text and produces text according to its architecture metadata on LLM.API.

Can I use tools or structured outputs with MiniMax Text 01?

Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.

How is MiniMax Text 01 priced on LLM.API?

Listed pricing metadata shows: In $0.2 / 1M tokens · Out $1.1 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

What are limitations of MiniMax Text 01?

Like other API models, MiniMax Text 01 can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

Is MiniMax Text 01 a chat model?

Yes—MiniMax Text 01 is exposed as a chat/completions-style endpoint on LLM.API.

Which endpoint do I call for MiniMax Text 01?

POST https://api.llmapi.ai/v1/chat/completions with model "minimax-text-01" and your LLM.API key. The request and response bodies are OpenAI-compatible.

How do I switch from OpenAI to MiniMax Text 01 on LLM.API?

Change two lines: set base_url to https://api.llmapi.ai/v1 and api_key to your LLM.API key. The rest of your OpenAI SDK code stays the same.

Does MiniMax Text 01 support function calling and structured outputs?

Function calling: supported via tools. Structured outputs: not supported.

MiniMax Text 01: Self-Hosting & Deployment Guide

MiniMax Text 01 brings MiniMax conversational intelligence to LLM.API so teams can ship assistants and agents without juggling multiple vendor SDKs.

Start Using API

What is MiniMax Text 01?

On LLM.API, MiniMax Text 01 (minimax-text-01) serves as a MiniMax conversational model for products that need 1M tokens context windows and predictable token pricing. minimax-text-01 provided by minimax. It is wired for API access through LLM.API with OpenAI-compatible patterns.

How to run MiniMax Text 01 yourself

Open weights, 456.1B parameters. Below: how much memory the weights need at each quantization, which hardware fits them, and the commands to serve it.

MiniMax Text 01 VRAM requirements

Precision / quantization	Weights	Figure	Source
BF16 (full precision)	912.2 GB	Estimate	456.1B params × 2 bytes

File size = actual download size on Hugging Face. Estimate = parameter count × bytes per weight. Weights only — the KV cache for long contexts needs extra memory; the fit tables below add 15% headroom as a rule of thumb.

GPU requirements: deploy MiniMax Text 01 on your hardware

Datacenter GPUsCloud instances

Hardware	BF16 (full precision)
NVIDIA H200141 GB	8×
NVIDIA H10080 GB	—
NVIDIA A100 80GB80 GB	—
NVIDIA L40S48 GB	—

GPUs needed per variant.

Hardware	BF16 (full precision)
AWS p5.48xlarge8× H100 · 640 GB	—
AWS p4de.24xlarge8× A100 80GB · 640 GB	—
AWS g6e.12xlarge4× L40S · 192 GB	—
Google Cloud a3-highgpu-8g8× H100 · 640 GB	—
Azure ND H100 v58× H100 · 640 GB	—

Whole-instance GPU memory; public instance specs.

Serve it yourself

vLLMSGLang

pip install -U vllm
vllm serve MiniMaxAI/MiniMax-Text-01

pip install 'sglang[all]'
python -m sglang.launch_server --model-path MiniMaxAI/MiniMax-Text-01

Commands use the official repositories above; vLLM and SGLang expose an OpenAI-compatible endpoint.

Skip the deploy — use LLM.API as your endpoint

No GPUs, no quantization trade-offs. Same model, OpenAI-compatible, up to 30% below list price.

Get API key See API code ↓

Providers

LLM.API routes MiniMax Text 01 to the providers below, with discounted effective rates versus list price.

List price by provider

InputOutput

minimax$0.2 in

$1.1 out

Provider list prices; the LLM.API discount applies on top.

Provider	Pricing	Context	Capabilities
minimax	in $0.2; out $1.1 per 1M tokens	1M tokens	tools, streaming

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 8 Oct 2026.

Try this model

Test MiniMax Text 01 right here — free to start.

MiniMax Text 01

Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call MiniMax Text 01 through the OpenAI-compatible API — POST /v1/chat/completions.

Switching from OpenAI? Change 2 lines.

- base_url="https://api.openai.com/v1"
- api_key="YOUR_OPENAI_KEY"
+ base_url="https://api.llmapi.ai/v1"
+ api_key="YOUR_LLMAPI_KEY"

Everything else stays the same — SDK, message format, tools, streaming. Set model to minimax-text-01 and the call runs unchanged.

bash

curl https://api.llmapi.ai/v1/chat/completions \
  -H "Authorization: Bearer $LLMAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "minimax-text-01",
    "messages": [
      {"role": "user", "content": "Give me three crisp launch checklist items."}
    ]
  }'

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAPI_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="minimax-text-01",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
)
print(resp.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.LLMAPI_KEY,
  baseURL: "https://api.llmapi.ai/v1",
});

const resp = await client.chat.completions.create({
  model: "minimax-text-01",
  messages: [
    { role: "user", content: "Give me three crisp launch checklist items." },
  ],
});

console.log(resp.choices[0].message.content);

stream = client.chat.completions.create(
    model="minimax-text-01",
    messages=[{"role": "user", "content": "Write a haiku about latency."}],
    stream=True,
)

for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)

{
  "model": "minimax-text-01",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

ENDPOINTS

Supported endpoints & features

Base URL https://api.llmapi.ai/v1 · model ID minimax-text-01 · OpenAI-compatible.

POST /v1/chat/completionsChat Completions — supported

Feature	Status	How to set it
Function calling (tools)	Supported	`tools, tool_choice`
Parallel tool calls	Not supported	`parallel_tool_calls`
JSON mode	Supported	`response_format: {"type": "json_object"}`
Structured outputs	Not supported	`response_format: {"type": "json_schema", …}`
Streaming	Supported	`stream: true`
Vision (image input)	Not supported	`image_url content parts`
Web search	Not supported	`web_search`

ERRORS

Errors & fallback routing

Code	What it means	What to do
`401`	Missing or invalid API key.	Send `Authorization: Bearer YOUR_LLMAPI_KEY` and check the key is active.
`429`	Rate limited, or the upstream provider is throttling the request.	Back off and retry with jitter; the gateway also retries the request on another provider where one is available.
`5xx`	Upstream provider error or timeout.	Retry; fallback routing sends the retry to the next healthy provider for this model.

When a provider fails or throttles, the request is routed to the next provider serving this model — the ones listed in the providers table above.

MiniMax Text 01 in production

Best workloadsLLM.API features

What the model is good at.

Instruction following
Follows detailed system and user instructions with strong adherence to format and tone. Relevant for `minimax-text-01` workloads on LLM.API.
Safety-aware replies
Supports product policies with refusals and cautious handling of sensitive topics. Relevant for `minimax-text-01` workloads on LLM.API.
Code assistance
Helps write, explain, refactor, and debug application code across common languages.
Multi-step reasoning
Breaks down complex problems into intermediate steps before answering. Reflects MiniMax positioning for this endpoint.
Conversational UX
Maintains coherent multi-turn assistant behavior for product chat surfaces. Reflects MiniMax positioning for this endpoint.

What you get when you call MiniMax Text 01 through LLM.API.

Unified AI Routing
Production: Reach MiniMax Text 01 and sibling models through one OpenAI-compatible endpoint.
One endpoint, every model.
Cost Control
Compare provider price points and keep spend visible as you scale MiniMax Text 01.
More performance, less spend.
Reliability Layer
Retry and route across configured providers when a single upstream blips.
Never go dark on users.
Observability
Trace prompts, tokens, and errors for MiniMax Text 01 alongside the rest of your stack.
See every token, everywhere.
Drop-in SDKs
Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Think tasks, not models.
Model Breadth
Practical: Swap MiniMax Text 01 for chat, media, or embedding alternatives without rewriting auth.
Scale from 1 to millions.

When to Use — When NOT to Use

Use it if...

You need provider failover options exposed for this model id (MiniMax Text 01)
You need a general-purpose text model for assistants, agents, or content workflows (MiniMax Text 01)
Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (MiniMax Text 01)
You want OpenAI-compatible chat completions through a single LLM.API key (MiniMax Text 01)

Avoid if...

You require on-prem only deployment with no cloud inference
You need pure embedding, OCR, or media generation instead of chat
You need guaranteed real-time hard latency SLAs without benchmarking the provider
Your use case depends on unpublished proprietary benchmarks not listed here

LLM API rating for MiniMax Text 01

★ 3.4/ 5.0LLM API rating
50% production adoption · 30% category benchmark · 20% tooling & valueEstimated from published specs

3.5Production adoptionActive open-weight community usage

2.8Benchmark qualityNo public Arena rank — scored on declared reasoning support

4.1Developer ecosystemContext window, tool and JSON support, price against the category median

Reasoning & chat 3.4Coding 4.0Tool & function calling 4.1Long context 4.1

How is this rating calculated?

Every model gets a separate 1.0–5.0 score for each category it can be used in, so a model can rate high for coding and lower for vision. The score combines three parts:

Production adoption — 50%. How widely the model is actually used in production: provider traffic, LiteLLM and gateway usage, open-weight downloads and its LMArena rank. Proven, widely used models score highest.
Category benchmark — 30%. The public benchmark that matters for that category — the Artificial Analysis Intelligence Index and LMArena Elo for reasoning, LMArena coding Elo for coding, image and document support plus vision Elo for vision, tool and JSON support for function calling, measured speed for voice.
Tooling & value — 20%. Context window, support for tools, structured outputs and streaming, and price compared with the category median.

Scores of 4.0 and above are shown in green, 3.0–3.9 in yellow, below 3.0 in red. When a model has no public data for a part, it gets a neutral value instead of an invented number.

A “Verified benchmark” mark (✓) means an independent lab — LMArena or Artificial Analysis — has actually tested that model, and the source figure is shown. Models without that mark are labelled “Estimated from published specs”: the score comes from the published context window, tool and schema support, price and adoption only, because no independent lab has tested them yet.

One exception: a brand-new top-tier model that scores very high on the independent benchmarks but has no usage history yet is rated on the benchmark (60%) and tooling & value (40%) alone, so a missing adoption figure can't hold it back. All inputs come from public sources and are refreshed weekly.

Adoption and benchmark inputs come from public sources — LMArena, Artificial Analysis Intelligence Index and published model specs. Updated weekly.

COMMUNITY

What developers say about MiniMax models

LMArena—Speed—Sources: LMArena, Artificial Analysis

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to MiniMax Text 01.

MiniMax M2 debuted as one of the highest-scoring open-weight models for coding and agentic tasks and is repeatedly recommended as a cheap Claude alternative.
Large-sample community tests (1,000+ prompts) report reliable tool calling and fast, shippable code.
Reviewers note it has since been overtaken by larger open-weight releases on general intelligence indices.

SOURCES

Frequently Asked Questions

Does MiniMax Text 01 support streaming?
Yes—at least one listed provider advertises streaming.
What is the context length for MiniMax Text 01?
Reported context for MiniMax Text 01 is 1M tokens. Always verify the active provider row if multiple providers are listed.
What is MiniMax Text 01?
minimax-text-01 provided by minimax. It is wired for API access through LLM.API with OpenAI-compatible patterns. On LLM.API it is addressed as `minimax-text-01`.
When should I choose MiniMax Text 01?
You need a general-purpose text model for assistants, agents, or content workflows — especially when you specifically need MiniMax Text 01.
Where is the canonical page for MiniMax Text 01?
https://llmapi.ai/models/minimax-text-01/
Which providers serve MiniMax Text 01?
LLM.API currently lists: minimax. Availability can vary by region and account.
How do I call MiniMax Text 01 via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "minimax-text-01" and your LLM.API key. See the code snippet on this page.
What modalities does MiniMax Text 01 support?
MiniMax Text 01 accepts text and produces text according to its architecture metadata on LLM.API.
Can I use tools or structured outputs with MiniMax Text 01?
Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.
How is MiniMax Text 01 priced on LLM.API?
Listed pricing metadata shows: In $0.2 / 1M tokens · Out $1.1 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.
What are limitations of MiniMax Text 01?
Like other API models, MiniMax Text 01 can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.
Is MiniMax Text 01 a chat model?
Yes—MiniMax Text 01 is exposed as a chat/completions-style endpoint on LLM.API.

COMPARE

Competitive Models

Get one key to every model

Swap your API key. Keep your code.

Start for free Talk to sales

LLM API sells to AI agents - live prices and self-serve payment

MiniMax Text 01: Self-Hosting & Deployment Guide

What is MiniMax Text 01?

How to run MiniMax Text 01 yourself

MiniMax Text 01 VRAM requirements

GPU requirements: deploy MiniMax Text 01 on your hardware

Serve it yourself

Providers

Try this model

Code snippet

Supported endpoints & features

Errors & fallback routing

MiniMax Text 01 in production

Instruction following

Safety-aware replies

Code assistance

Multi-step reasoning

Conversational UX

Unified AI Routing

Cost Control

Reliability Layer

Observability

Drop-in SDKs

Model Breadth