MiniMax M2.1
MiniMaxhuggingface.co/MiniMaxAI/MiniMax-M2.1
MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world...
Updated 6 h ago · first seen 11 Sept 2026
model_01M294WW6Q1EGFNFNV6JFJVEPB
Overview
Identity
Identity block not returned by the API for this entity.
Openness
Openness not classified yet — no sourced evidence to place this model in the ontology.
Key facts
- Release date
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 8 h agomedium
- Status
Source:Artificial AnalysisT2observed 11 h agomedium
- Model card
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Openrouter id
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
Architecture
- Architecture
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Model type
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Parameters
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Weights dtype
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- File size
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Library name
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium
- Pipeline tag
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Hugging Face repo
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
Capabilities
Modalities
- Modalities
- text
- Input
- text
- Output
- text
Capabilities
Tool calling
Yes
OpenRouter public model & pricing listing · T2
Structured output
Yes
OpenRouter public model & pricing listing · T2
Reasoning
Yes
OpenRouter public model & pricing listing · T2
Vision
Unavailable
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
- Max output
Source:OpenRouter public model & pricing listingT2observed 13 h agomedium
Benchmarks6
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
No benchmark results recorded
Providers & Pricing1
All offers in the price terminal →USD per 1M tokens as published by each provider (USD). Rows are append-only: every change is kept in the history below.
Price history
Output price · USD / 1M tokens 1 provider
- MiniMax API
- MiniMax APIfirst observed $1.211 Sept 2026
Input price · USD / 1M tokens 1 provider
- MiniMax API
- MiniMax APIfirst observed $0.3011 Sept 2026
Hardware fit37
Assumptions (6)
- Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead.
- bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
- KV cache approximated at 0.5 GB per 8 192 tokens of context, independent of architecture (GQA/MLA models need less).
- A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
- Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
- Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).
Lineage
Open in Graph →Papers1
- arXiv:2509.06501Active35
Timeline10
Full timeline →MiniMax M2.1 scores 28.79% on Terminal-Bench
artificial_analysisMiniMax M2.1 scores 23.17% on Humanity's Last Exam
artificial_analysisMiniMax M2.1 scores 20.95 on Artificial Analysis Intelligence Index
artificial_analysisMiniMax M2.1: release date changed from 2025-12-20 to 2025-12-23
Release date20 Dec 2025→23 Dec 2025openrouterMiniMax M2.1: release date changed from 2025-12-23 to 2025-12-20
Release date23 Dec 2025→20 Dec 2025huggingfaceMiniMax API lists MiniMax M2.1 at $0.3 in / $1.2 out per 1M tokens
openrouter
Change history39
Viewing AI Atlas as of 12 Mar 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →MiniMax M2.1 was not yet in AI Atlas on 12 Mar 2026
Release daterelease_date4
Statusstatus1
Opennessopenness1
Licenselicense1
Architecturearchitecture1
Parametersparameter_count1
Context windowcontext_length1
Max outputmax_output_tokens1
Modalitiesmodalities1
Input modalitiesmodalities_input1
Output modalitiesmodalities_output1
Quantization formatquant_format1
File sizefile_size_gb1
Hugging Face repohf_repo1
Pipeline tagpipeline_tag1
Model cardmodel_card_url1
Downloadsmetric.downloads1
Likesmetric.likes1
Descriptiondescription1
Gatedgated1
Hf inference providershf_inference_providers1
Is quantizedis_quantized1
Last modifiedlast_modified1
Library namelibrary_name1
License namelicense_name1
License urllicense_url1
Aa median output tokens per secondmetric.aa_median_output_tokens_per_second1
Downloads all timemetric.downloads_all_time1
Model typemodel_type1
Openrouter idopenrouter_id1
Reasoningreasoning1
Structured outputstructured_output1
Supported parameterssupported_parameters1
Tool callingtool_calling1
Weights dtypeweights_dtype1
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
Provenance
Attributed facts
37
Source tiers
T237
Freshest observation
6 h ago
Conflicts
None
Source documents 6
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (68/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →