MiniMax releases M2.5, claiming the model delivers on the “intelligence too cheap to meter” promise, priced at $0.30/1M input tokens and $1.20/1M output tokens
MiniMax had already positioned its model line around coding and builder use, including an M2.1 coding upgrade and the earlier open-source M1 release for complex productivity work. M2.5 makes the next competitive variable explicit: token pricing alongside claimed capability.
Later coverage extends that trajectory from M2.5 to a self-evolving M2.7 system and then a lower-cost M3 coding model. That sequence makes M2.5 relevant as an early marker of MiniMax's effort to pair rapid model iteration with lower inference prices.
First-order effects
MiniMax gives API buyers a stated M2.5 price of $0.30 per million input tokens and $1.20 per million output tokens, lowering the quoted cost basis for workloads that can use the model.
The company ties its reinforcement-learning-trained release to an “intelligence too cheap to meter” positioning, putting price-performance—not model availability alone—at the center of its pitch.
Second-order effects
Competing model vendors face more pressure to justify higher token rates with measurable capability, reliability, or tooling advantages, particularly for coding and high-volume applications.
Buyers can more readily test multi-model routing and expand token-intensive use cases when a lower published price broadens the range of economically viable workloads.
Third-order effects
If capable models continue to fall in price, model differentiation may shift toward performance on specific tasks, integration, and operational control rather than baseline token cost.
Sustained price compression would also sharpen the tension between low-cost inference offers and the compute required to train and serve increasingly capable models.
The trend: M2.5 is part of the shift from frontier-model scarcity toward competition on the cost per useful AI task.
Introducing M2.5, an open-source frontier model designed for real-world productivity. - SOTA performance at coding (SWE-Bench Verified 80.2%), search (BrowseComp 76.3%), agentic tool-calling (BFCL 76.8%) & office work. - Optimized for efficient execution, 37% faster at complex [i…
@MiniMax_AI M2.5 performed particularly well on long-running tasks like building apps from scratch, an area where smaller models have traditionally struggled. Also strong on issue resolution and software testing. [image]
interesting thing about minimax 2.5 is it's a smaller model considering it's very usable it's a great candidate for home labs also would love to see inference providers try and max out its tokens/s can probably do something crazy [image]
With M2.5 we're also shipping MiniMax Experts. general agents sound nice until you realize they don't know your stack, your domain, or how you actually work. now you can build experts that do. share yours, grab others'. community already made: clawbot assistant, crypto trading
Zen × MiniMax M2.5 - free for a week wait what.. 2.5?! yes sir.. feels like M2.1 just dropped yesterday and now it's already M2.5?! better try it before M2.67 shows up next month
Love seeing the benchmarks out in the wild 🚀 MiniMax M2.5 was built for real-world, long-horizon agent workloads - Reliability + performance both matter. Thanks for sharing! 🙌
China won. This is another deepseek moment MiniMax 2.5 is now the best model in the world > On par with opus 4.6 > SOTA in coding, excel data analysis, deep research, document generation and summarization > Optimized thinking efficiency + 100 tps to achieve 3x faster than opus [i…
MiniMax M2.5 is live now on OpenRouter! @MiniMax_AI's update to their powerful agentic model M2.1 comes with improved reliability and performance on long running tasks. It's become a powerful general agent, capable of much more than writing code. [image]
To be honest, I'm a bit of a skeptic of claims that models are on par with Claude/GPT, but this is definitely one that I feel is getting there. Especially for tasks that focus on code (as opposed to other things like writing, math, etc.) More in the thread above.
minimax 2.5 is now generally available and free for 7 days in opencode i'm going to try and switch to it as my default so i can get a sense of how it works golden era for opensource models right now
MiniMax-M2.5 is a surprising new step in open coding models. The first model where I've been able to independently confirm that it's better than the most recent Claude Sonnet. It showed up in our benchmarks below, and in my vibe checks it felt strong and diverse.
@MiniMax_AI At 230B parameters (10B active), it's also relatively lightweight for a frontier-class model. This is the size where local deployment is feasible as well. [image]
BREAKING: MiniMax just dropped official M2.5 benchmarks and they're going HEAD TO HEAD with Opus 4.6, GPT-5.2, and Gemini 3 Pro 🤯 And Olive Song from @MiniMax_AI is joining ThursdAI LIVE in ~30 min to break it all down @ThursdAI_pod Here are the numbers 👇 [image]
@MiniMax_AI The cost-performance tradeoff is remarkable. At ~13x cheaper than Opus, M2.5 opens up use cases that weren't practical before. It's essentially a two-horse race for API-available models at the moment: Opus for max capability, M2.5 for high capability at low cost. [ima…
Big news for open models: @MiniMax_AI M2.5 is out and it's an excellent+affordable coding model. It ranks 4th in our benchmarks, the first open model to beat Claude Sonnet. Only Claude Opus and GPT-5.2 Codex score higher. Details on scores and limited-time free access below 🧵 [im…
🧠 Meet Expert Collection from MiniMax Agent A team of specialized AI experts — office productivity in docs, Excel, PDFs & slides, finance in research & McKinsey-style decks, and coding — working together inside MiniMax Agent. Test directly with our showcase queries or bring [vide…