Models / MiniMax/ MiniMax-01

MiniMax-01

MiniMax · released Jan 12, 2025 · MiniMaxAI/MiniMax-Text-01

Input: text and images. Output: text.InputOutput
Type
Open weights
Params
456B
Context
1M

about 750K words of context

Our take

Written Aug 2, 2026

MiniMax-01 is a 456.1-billion-parameter text-and-image model with a one-million-token request limit, released in early 2025. Its weights can be downloaded, though the licence terms are undisclosed, and no benchmark scores are available to verify its quality.

Who should pick it

Choose this when you need downloadable weights and the longest context window available — over one million tokens — for long-document work or video-frame analysis. It is a budget-conscious option for such tasks. Skip it if you need verified quality scores, if you require a known licence for commercial use, or if you need reliable throughput across multiple providers.

The case for it

  • Extremely long context window among downloadable models: 1,000,192 tokens.
  • Open weights at moderate per-token pricing, with 456.1 billion parameters available for local deployment.

The case against it

  • No measured quality or performance data in our catalogue: zero benchmark scores, no chat Elo, no reasoning or coding scores.
  • Throughput data is thin and partially unverified: only 29 tokens per second on one provider, unverified on the other.
  • Licence terms are undisclosed, so commercial use, redistribution and modification rights are unverified.
00

How good is it?

We hold no score for this model.

We look for every model we track on every board we watch, and none of them has turned up MiniMax-01 — so there is no intelligence, coding, agentic or writing score to show you, not a low one, none.

The boards we watch →

01

Can you run it yourself?

Fits in memory
weights load entirely on the card
Spills to system RAM
some weights offload; much slower
Too large
will not load even with offload
est
size is calculated; the verdict could change by 10%
A card many people ownToo large

GeForce RTX 4090 · 24 GB

Weights at Q4_K_M287.6 / 24 GBest
Usable contextNot calculated for spilled setups
Decode speedNot estimated for spilled setups

Too large for this card. The weights do not fit even with part of them offloaded to system memory.

One step upToo large

Apple M1 Pro (16-core GPU) · 32 GB

Weights at Q4_K_M287.6 / 32 GBest
Usable contextNot calculated for spilled setups
Decode speedNot estimated for spilled setups

Too large for this card. The weights do not fit even with part of them offloaded to system memory.

Comfortable fit

On a MacFits in memory

Apple M3 Ultra (80-core GPU) · 512 GB

Weights at Q4_K_M287.6 / 512 GBest
Spare memory85.9 GB spare
Usable context262K of 1M
Decode speed2 tok/sest

Room to spare. 85.9 GB spare means a 10% error in the size would not change the answer.

Your hardware
Checking your profile…

Memory use by level

Against a 24 GB card.

Q4_K_M
recommended
287.6 GBest
Too large
Q5_K_M
337.4 GBest
Too large
Q8_0
504 GBest
Too large

All 3 sizes here are calculated, not measured. We hold no measured file for this model, so each size comes from the parameter count and every verdict above inherits that uncertainty.

Check against your own machine → · All 71 devices, with every size →

02

Or rent it from someone else

Cheapest published offer

Cheapest of 2 live listings. Picked at the widest standard context we hold, within one quantisation slice, so the numbers beside it are a price one host actually charges.

per 1M tokens
$0.20 in / $1.10 out
Context served
1M
Throughput
Not measured
Current provider offers with price, context and prompt-privacy answers
ProviderIn / out per 1M tokensContextThroughputTrains on promptsLogs promptsZero retention
OpenRouter$0.20 / $1.101Mnot measuredUnknownUnknownUnknown
Minimax$0.20 / $1.101M27 tok/sNoYesunknown periodUnknown

Across the 2 listings we hold: 1 say they do not train on prompts, 0 say they do and 1 do not say. 0 appear in the zero-retention registry we check; the rest are unknown to us rather than confirmed either way.

What each host's API supports

From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.

Supported
Not supported
Not published
host gave no parameter list
API features per host
ProviderTool callingJSON outputStrict schema
OpenRouter
Minimax

Tool calling: 0 of 2 listings say yes, 2 say no. JSON output: 0 of 2 listings say yes, 2 say no. Strict schema: 0 of 2 listings say yes, 2 say no.

03

When we formed this view

Dates behind this page

Jul 26, 2026ListedListed on LLMapfirst indexed by our pipeline
Jan 12, 2025AnnouncedMiniMax-01 announced by MiniMax

Prices last checked 3d ago

What we do not know about this model yet

  • We hold no measured file for it, so all 3 sizes on this page are calculated from the parameter count.
  • No board we watch has turned up a score, so we hold no quality figures at all.
  • Nothing we hold says whether an endpoint streams, so we do not show it either way.
  • 1 of 2 listings do not say whether they train on prompts.
  • We hold no cached-input rate for any of its listings.
04

Licence and identifiers

What the licence allowsWe hold no licence record for this model. Inside are the identifiers you need to pull it — its Hugging Face repo where we have one, our slug and a machine-readable card.

Licence

We hold no licence record for this model yet.

Identifiers

Architecture
Mixture of experts
Modality record
text+image->text
Catalogue slug
minimax-minimax-01

Machine-readable model card (omc.json) →

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