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MiniMax M1

MiniMax

MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...

quality50

Updated 6 h ago · first seen 11 Sept 2026

model_01M294WWFC8JMJMQ54BY9KGHAD

Context
1M tokens
T2 · 6 h ago
Released
17 Jun 2025
T2 · 6 h ago
Knowledge cutoff
Jun 2024
T2 · 6 h ago

As of

Rewind the record: see this entity's attributes exactly as AI Atlas knew them on a given day.

Claim history · Supported parameters

1 claims · 1 propertiesShow all properties

Supported parameterssupported_parameters1

Claim history for Supported parameters
ValueValid from → toStatusSourceConfidenceExtractor
frequency_penalty, include_reasoning, max_tokens, presence_penalty, reasoning, repetition_penalty, seed, stop, temperature, tool_choice, tools, top_k, top_pcurrentcurrentOpenRouter public model & pricing listingT2mediumdeterministic

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 →