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Model details

Minimax M2.1

Minimax M2.1 sits within a broader MiniMax lineup that the company publicly tracks on its news site and API documentation, where the headline framing presents it as a model emphasizing significantly enhanced multi-language programming and real-world complex task handling. The announcement page is titled to that effect, positioning M2.1 as part of a development lineage that, in surrounding MiniMax documentation, includes successors such as M2.5 and M2.7 alongside the newer M3 frontier coding release. Within that lineage, M2.1 reads as an earlier-generation coding-focused variant aimed at developers who need solid polyglot code generation and refactoring support, with the broader family known for engineering-oriented strengths and progressively expanded context capabilities.

For practitioners, the practical framing of M2.1 is that of a coding-centric large language model intended for real-world development workflows, including multi-language code generation and targeted refactoring work. The MiniMax family surrounding it advertises features such as polyglot code mastery and precision code refactoring on its official documentation, and M2.1's announcement theme aligns with that engineering-focused direction, making it a reasonable fit for teams seeking a coding assistant rooted in a model family with a track record of incremental improvements across versions. Users evaluating it should weigh it against the newer M2.5 and M2.7 variants, which MiniMax documents more extensively and which may offer expanded capabilities, while M2.1 represents the earlier point in that coding-focused trajectory.

Jiekou.AIminimax/minimax-m2.1minimax

Quick Info

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Provider
Jiekou.AI
Model key
minimax/minimax-m2.1
Release date
Jan 1, 2026
Last updated
Jan 1, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.30
Output token cost
$1.20

Limits

Output tokens
131,072 tokens
Context window
204,800 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about Minimax M2.1

Vercel AI Gateway

Official sourceAnnouncement

On January 22, 2026, MiniMax published a follow-up post on minimax.io titled "MiniMax M2.1: Post-Training Experience and Insights for Agent Models," explicitly naming MiniMax M2.1 as the subject and describing it as the latest flagship open-source model built on further post-training optimization over the M2 generation The same post breaks down M2.1's agentic data synthesis into three categories: real-data-driven synthesis called SWE Scaling, expert-driven synthesis for AppDev, and virtual long-horizon task synthesis called WebExplorer. SWE Scaling is described as leveraging GitHub pull requests and commits as a structured data sourc

Jiekou.AI

CoverageRelease Notes

The Opper release tracker provides the cleanest dated reference for MiniMax M2.1, confirming its release date as December 23, 2025, a 205K context window, $0.30 per million input tokens and $1.20 per million output tokens pricing, and an Artificial Analysis intelligence index of 32. This positions M2.1 as the December Beyond M2.1 itself, the tracker also documents the broader M-series context relevant to developers evaluating Jiekou.AI's M2.1 offering: M2.5 (Feb 2026, 66K ctx, $0.30/$1.20, intelligence 35), M2.7 (Mar 2026, 197K ctx, $0.25/$1.00, intelligence 39), and M3 (Jun 2026, 512K ctx, $0.30/$1.20, intelligence 45) all postdate

Vercel AI Gateway

CoverageBenchmark

Kilo Code's product page at kilo.ai/models/minimax-minimax-m2-1 explicitly names MiniMax-M2.1 as a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development, noting that with only 10 billion activated parameters it delivers a major jump in real-world The same page reports Kilo Code's PinchBench (OpenClaw) results for MiniMax-M2.1: an average score of 82.7% across 17 of 50 official models, average time of 19m 51s across 33 runs per OpenClaw task, and average cost of $0.168 per benchmark run. Category breakdown shows the best verified PinchBench v2 run scoring 95.1%

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