MiniMax-M3.1-Flash scores 42 on Artificial Analysis Index
Efficiency is the headline: the model used ~189M output tokens versus 324M for GLM-5.3-Flash, so low cost comes from token frugality as much as pricing. Its 93% hallucination rate on AA-Omniscience means teams should add verification layers for factual workloads. An open-weights release on 23 October 2026 would make it directly comparable with DeepSeek's open models for ASEAN startups building on local hosting.
MiniMax-M3.1-Flash, MiniMax's new Flash reasoning model, scores 42 on the Artificial Analysis Intelligence Index, 13 points above MiniMax-M3. It matches GLM-5.3-Flash (42), edges Gemini 3.8 Flash (41), and trails DeepSeek V4.1 Flash 1017 (45). It scores 48% on Humanity's Last Exam and 22% on CritPt, up from 39% and 4% for M3. Its cost per Intelligence Index task is ~$0.22 at $0.15/$0.60 per 1M input/output tokens, versus ~$1.24 for Gemini 3.8 Flash. Open weights are announced for 23 October 2026.
MiniMax-M3.1-Flash scores 42 on the Artificial Analysis Intelligence Index, 13 points higher than MiniMax-M3 and less than half the cost per task. It scores level with GLM-5.3-Flash but behind DeepSeek V4.1 Flash 1017
MiniMax-M3.1-Flash is @MiniMax_AI's new Flash reasoning model, which we benchmarked at its max effort setting. It scores 42 on the Artificial Analysis Intelligence Index, level with GLM-5.3-Flash (max, 42), just ahead of Gemini 3.8 Flash (high, 41), and behind DeepSeek V4.1 Flash 1017 (max, 45)
Key takeaways: ➤ Complex reasoning improved substantially compared to M3: MiniMax-M3.1-Flash scores 48% on Humanity's Last Exam, ahead of GLM-5.3-Flash (max, 40%) and DeepSeek V4.1 Flash 1017 (max, 43%), and level with Gemini 3.8 Flash (high, 48%). On CritPt it scores 22%, ahead of GLM-5.3-Flash (15%) and Gemini 3.8 Flash (18%) and just behind DeepSeek V4.1 Flash 1017 (24%). These are up from MiniMax-M3 which scored 39% and 4% respectively
➤ Fewer output tokens, lower cost per task: MiniMax-M3.1-Flash used ~189M output tokens to run the Intelligence Index, considerably fewer than GLM-5.3-Flash (max, ~324M), DeepSeek V4.1 Flash 1017 (max, ~224M) and Gemini 3.8 Flash (high, ~334M). Combined with pricing of $0.15/$0.60 per 1M input/output tokens, this brings its cost to ~$0.22 per Intelligence Index task, vs ~$0.28 for GLM-5.3-Flash, ~$0.26 for DeepSeek V4.1 Flash 1017 and ~$1.24 for Gemini 3.8 Flash, and less than half MiniMax-M3's ~$0.51
➤ High AA-Omniscience accuracy, offset by a high hallucination rate: MiniMax-M3.1-Flash answers 56% of questions correctly on AA-Omniscience, our benchmark measuring factual recall and hallucination, vs 28% for GLM-5.3-Flash (max) and 43% for DeepSeek V4.1 Flash 1017 (max). It attempts almost every question, resulting in a hallucination rate of 93% and an overall score of 16 on AA-Omniscience
Key model details:
➤ Context window: 1M tokens
➤ Multimodality: Text and image input, text output
➤ Pricing: $0.15/$0.60 per 1M input/output tokens, with cached input at $0.015/M
➤ Availability: MiniMax first-party API, with MiniMax announcing an open weights release on October 23rd
➤ Licensing: Closed weights currently, with MiniMax announcing a weights release on October 23rd
