MiniMax-M1 and MiniMax Agent: China’s Biggest Open-source Reasoning Model and Agent

The Chinese language AI firm, MiniMaxAI, has simply launched a large-scale open-source reasoning mannequin, named MiniMax-M1. The mannequin, launched on Day 1 of the 5-day MiniMaxWeek occasion, appears to provide a very good competitors to OpenAI o3, Claude 4, DeepSeke-R1, and different contemporaries. Together with the chatbot, MiniMax has additionally launched an agent in beta model, able to working code, constructing apps, creating displays, and extra. On this article, we’ll discover the important thing options of MiniMax-M1, learn to entry it, and try it out on just a few duties. We’ll even be exploring the MiniMax Agent, so learn until the top to observe the agent in motion!

What’s MiniMax-M1?

MiniMax‑M1 is an open‑supply, giant‑scale, hybrid‑consideration reasoning mannequin, developed by Shanghai‑based mostly AI startup MiniMax. The pondering mannequin comes with an internet search characteristic and may deal with multimodal enter within the type of textual content, pictures, displays, and extra throughout varied codecs.

Constructed on a Combination‑of‑Specialists (MoE) structure, the mannequin is skilled on a complete of 456 billion parameters, with about 45.9 billion activated per token. Furthermore, the mannequin is launched beneath an Apache 2.0 license, making it really open-source.

MiniMax has launched Lightning Consideration for its M1 mannequin, dramatically lowering inference prices. To place it in numbers, it makes use of simply 25% of the FLOPs in comparison with DeepSeek‑R1 at 100,000‑token era. The mannequin is skilled by way of giant‑scale RL utilizing CISPO (Clipped Significance Sampling Coverage Optimization), which clips sampling weights as an alternative of updates. This led to environment friendly coaching on 512 A800 GPUs over 3 weeks, costing solely round $534,700. That is far decrease than the tens of millions spent by rivals like OpenAI and Google.

Key Options

Listed here are the important thing options of the brand new MiniMax-M1 mannequin:

1. Hybrid Consideration + MoE Effectivity: M1 combines an MoE structure with Lightning Consideration, reaching as much as 75% compute financial savings in comparison with most different fashions.
2. Massive Contect Window: M1’s greatest spotlight is its large context window of 1M enter token tokens and upto 80k output tokens, rivaling Google’s Gemini 2.5 Professional.  
3. Obtainable in 40k & 80k Considering Budgets: MiniMax gives M1‑40k (intermediate) and M1‑80k (superior) variations. The 80k variant performs higher on prolonged reasoning and sophisticated duties.
4. Prolonged Agentic & Lengthy‑Context Reasoning: The fashions benchmark performances present that it excels at long-context benchmarks (OpenAI‑MRCR, LongBench‑v2) and agentic device use (TAU‑bench).

Also Learn: New Deepseek R1-0528 Replace is INSANE

MiniMax‑M1: Benchmark Efficiency

Right here’s how the M1‑80k mannequin stacks up throughout main benchmark domains:

• AIME 2024: MiniMax-M1 achieved the best rating (86.0%), outperforming all proprietary fashions like OpenAI o3, Claude 4 Opus, and Gemini 2.5 Professional.
• LiveCodeBench: MiniMax-M1 scored 65.0% on this coding benchmark, simply barely behind OpenAI o3 and Gemini.
• SWE-bench Verified: On this software program engineering benchmark, MiniMax-M1 achieved 56.0%, clearly outperforming DeepSeek-R1 and Qwen3 by over 10%.
• TAU-bench: On the subject of agentic device use, MiniMax-M1 scored 62.8%, beating each DeepSeek and Qwen3. This reveals the mannequin’s robust tool-using functionality.
• MRCR: The MRCR benchmark checks the fashions’ abilities in multi-round doc evaluation and long-context reasoning. MiniMax-M1 scored 73.4% on the check, coming near high industrial fashions and much forward of different open-source ones.

Also Learn: What are LLM Benchmarks?

How one can Entry MiniMax‑M1

MiniMax‑M1 is absolutely open‑sourced and accessible on each GitHub and Hugging Face. You may also use the mannequin immediately on its chatbot interface: https://chat.minimax.io/.

The MiniMax API gives structured function-calling interfaces and different chatbot APIs as properly. It additionally offers instruments for search, picture/video era, voice synthesis, and voice cloning – now tailor-made for agentic workflows.

MiniMax-M1: Palms-on Testing

Now that we all know tips on how to entry MiniMax-M1, let’s strive it out. On this part, I’ll be testing out three completely different prompts to gauge the efficiency of the mannequin in:

1. Coding an animated simulation
2. Looking the net in real-time
3. Fixing a logical reasoning puzzle

Let’s get began!

Job 1: Animated Simulation

Immediate: “Generate a simulation of a purple pentagon, rotating clockwise inside a black hexagon. There are 2 balls transferring contained in the pentagon – one blue, one yellow – bouncing off of the partitions following the legal guidelines of Physics. Each time a ball hits an edge, its color should change. And each time they collide with one another, they need to each change into the combination of each their colors.”

Output

Assessment

In about 10 minutes, MiniMax-M1 generated clear and environment friendly code with correct explanations to create the simulation. It got here out to be visually clear and bodily correct, following the immediate precisely. The balls, nevertheless, get caught on the edges at instances, which I discovered to be an error. Also, the balls finally get thrown out of the simulation, which I didn’t anticipate. However on the entire, I did just like the end result.

Job 2: Internet Search

Now let’s see how properly the mannequin can search the net in real-time. On this job, I’m going to ask MiniMax M1 to seek out me occasions occurring this week in my metropolis. I’ll be turning on the ‘Search’ mode for this job.

Immediate: “What stand-up comedy reveals are occurring in Gurgaon this week?”

Output

Assessment

MiniMax M1 nearly instantly searched throughout 30 completely different web sites together with District, All Occasions, and even occasion listings on Fb and Instagram. It gathered all the information and gave me an inventory of all of the stand-up occasions occurring round. The search was carried out proper, however the mannequin was unable to learn or detect the timing and venue of the occasions. Nevertheless, it listed out all of the supply web sites on the right-hand facet, making it simpler to entry the reserving websites.

Job 3: Logical Puzzle

MiniMax M1 is a reasoning mannequin with pondering capabilities. So, I’m going to provide it a logical puzzle to resolve on this job. I’ll additionally activate the ‘suppose’ mode for this to see the mannequin’s pondering course of.

Immediate: “4 individuals are crossing a bridge at evening, so all of them want a torch – however they simply have one which solely lasts quarter-hour. Alice can cross in a single minute, Ben in two minutes, Cindy in 5 minutes and Don in eight minutes. Not more than two folks can cross at a time; and when two cross, they need to go on the slower individual’s tempo. How do they get throughout in quarter-hour?”

Output

“The optimum answer to get all 4 throughout in quarter-hour is as follows:

1. Alice and Ben cross collectively (2 minutes).
   Time elapsed: 2 minutes
   Folks on far facet: Alice, Ben
2. Alice returns alone (1 minute).
   Time elapsed: 3 minutes
   Folks on begin facet: Alice, Cindy, Don
3. Cindy and Don cross collectively (8 minutes).
   Time elapsed: 11 minutes
   Folks on far facet: Cindy, Don, Ben
4. Ben returns alone (2 minutes).
   Time elapsed: 13 minutes
   Folks on begin facet: Alice, Ben
5. Alice and Ben cross collectively once more (2 minutes).
   Time elapsed: quarter-hour
   All 4 on far facet: Alice, Ben, Cindy, Don

Key technique: Use the 2 quickest people (Alice and Ben) to shuttle the torch effectively, minimizing the time slower people (Cindy and Don) spend crossing collectively. This balances the necessity to transfer slower people whereas preserving torch time.”

Assessment

MiniMax-M1 took about 2 minutes (125.2 seconds to be exact) to consider the issue and determine the answer. The mannequin’s logical thought course of was on level, resulting in the proper reply. It didn’t need to backtrack any of the ideas, however at some factors, it took a bit longer to suppose.

MiniMax Agent in Motion

Now let’s get to the good a part of MiniMax’s new launches – the MiniMax Agent. Though presently in beta section, its capabilities and numerous use instances make it fairly promising on the earth of AI brokers. To check out its prowess, I gave it a immediate to construct me an interactive web site. Right here’s how that went.

Immediate: “Construct an interactive web site that includes a digital tour of India.

1. It should present the nation map with the states marked, letting the consumer learn the title of the state and the respective capital metropolis once they hover the mouse over it.
2. It should zoom into the chosen state upon clicking, exhibiting all of the well-known monuments and landmarks as consultant icons.
3. Once more, their names and site (title of metropolis) should be proven when hovered above the icon.
4. Upon clicking on an icon, a facet panel should pop up exhibiting precise pictures, the placement, visiting instances, and entrance charge of the landmark.
5. The consumer should have the choice of selecting a number of landmarks, and the app/web site should create a sensible itinerary of visiting all these locations, additionally stating what number of days it will take to cowl all of them. This should additionally think about the commute time based mostly on Google Maps.”

Output

And right here’s the web site it constructed for me:

Assessment

MiniMax Agent did an incredible job at creating an interactive web site to fulfill my necessities. Though the ultimate web site wasn’t precisely how I had defined in my immediate, I need to say the outcomes are spectacular. The agent discovered the information, added the textual content and pictures, obtained API keys, accessed Google Maps and different apps, constructed the entire system, and even examined it – all by itself. It took about 20 minutes to do the entire thing and even offered documentation of the method, check outcomes, and all different particulars. A free device doing all of this so properly, is simply mind-blowing!

You possibly can expertise the total web site right here: https://03w1ujb85t.house.minimax.io/

You may also check out the agent at no cost by clicking right here. When you join utilizing your e-mail ID, MiniMax offers you 1,000 free credit to spend on working the agent.

Conclusion

MiniMax‑M1 represents a significant leap in open-source AI. It’s a first-of-its-kind hybrid-attention MoE mannequin, combining scale and compute effectivity. With an astonishing 1M token context window, this new mannequin is able to long-form reasoning and doc understanding. Regardless of the low coaching prices, it reveals aggressive or superior efficiency throughout customary benchmarks.

The MiniMax Agent can also be fairly spectacular, with the ability to create displays, web sites, and apps by itself. The chatbot interface and stay updates on the facet give customers the sensation of vibe coding. On the entire, MiniMax‑M1 units a brand new customary in open-source mannequin improvement. Mixing technical sophistication, financial effectivity, and accessibility, it has constructed a robust basis for next-generation AI chatbots and brokers. Because it’s free to make use of for everybody, go forward, strive it out, and tell us within the feedback how you discover it.