MiniMax M2.7 on Genosai — agentic tasks and creative text for 0.5 credits
MiniMax M2.7 is a text MoE model from MiniMax, available on Genosai with a 125,000-token context. Of its 230 billion parameters, only about 10 billion are active per token, so it is fast and cheap — 0.5 credits per request. It is tuned for agentic workflows, tool use, and creative text, and runs online with no MiniMax account or API setup.
Updated: July 7, 2026
- 230B-parameter MoE — Only 10B of 230B parameters activate per token — big-model power with fast response times.
- 125,000-token context — The model holds long conversations, briefs, and documents whole without losing the thread from the start.
- Agentic workflows — 97% instruction adherence across 40+ complex skills — it holds multi-step tasks and tool use steadily.
- Strong coding — SWE-Pro 56.22% and Terminal Bench 2 57.0% — it writes, debugs, and carries projects to a working result.
- 0.5 credits per request — One of the most affordable models in the catalog — handy for high-volume, frequent tasks.
Contents
- What is MiniMax M2.7
- Capabilities
- Examples prompts and responses
- How to use on Genosai
- Prompts
- How it compares
- Limitations and tips
- FAQ
What is MiniMax M2.7
MiniMax M2.7 is a text model from MiniMax, released on March 18, 2026. It continues the MiniMax M2 line and leans into agentic scenarios: multi-step tasks, tool use, and carrying projects through to a result. On Genosai the model is available online, so you do not need a separate account, API keys, or your own infrastructure.
At its core is a Mixture-of-Experts architecture. The model holds 230 billion parameters and 256 experts in total, but only a small share fires per token — about 10 billion parameters and 8 experts. That is why MiniMax M2.7 answers fast and stays cheap: 0.5 credits per request, one of the lowest prices in the catalog. It makes the model handy for high-volume and frequent tasks.
What the MoE design means in practice. The model does not push every request through all 230 billion parameters — a router activates only 8 of 256 experts for each token. That yields a combination hard to get otherwise: fast responses and a low per-request price at the quality of a large model. This is why MiniMax M2.7 fits high-throughput tasks where both speed and budget matter.
What sets it apart from general chat models is specialization. MiniMax M2.7 is strong where instructions must hold across a long chain of steps: on 40+ complex skills the model shows 97% adherence to the task. It is confident in code too — SWE-Pro 56.22% and Terminal Bench 2 57.0%. At the same time it handles creative work well: headlines, checklists, and short posts. That profile makes it a solid pick for content pipelines and setups where one model both plans the steps and generates the text.
In terms of lineage, MiniMax M2.7 is a fresh iteration of the MiniMax M2 family with a focus on agentic scenarios and tool use. On Genosai you get it with no barrier to entry: no local hosting, no weights to manage, no idle server to pay for — just pick it in the text studio.
Capabilities
MiniMax M2.7 covers scenarios where structure, speed, and precise instruction-following matter. Here is what the model does well in practice.
Agentic and multi-step tasks
The model holds long chains of instructions and does not "forget" the condition by the end of an answer. It works through multi-step assignments carefully, keeps to the given format, and fits scenarios with tools and skills. That predictability at every step is exactly why teams reach for MiniMax M2.7.
Code and data
MiniMax M2.7 writes and reviews code, debugs errors, and helps bring a small project to a working state. Its coding benchmark scores confirm the model is fit for more than drafts: SWE-Pro 56.22%, Terminal Bench 2 57.0%, and 76.5 on multilingual SWE. It explains its solutions, keeps the output structured, and works well in scenarios where code comes paired with terminal commands or a sequence of actions.
Creative content
The model quickly generates headlines, slogans, posts, and checklists. It offers several options to choose from and formats the answer neatly in Markdown — with lists, subheadings, and checkboxes. For content tasks that need volume and speed, it is a handy and inexpensive tool. When you need a batch of variants to test — say ten subject lines or five hooks — the low per-request price makes it easy to generate widely and keep only the best.
Structure and formatting
MiniMax M2.7 keeps the structure you ask for: request a five-step checklist and you get exactly five blocks with items. It adds dividers, emphasis, and lists where they fit, and returns publish-ready text with no manual format cleanup. That saves time on content tasks: the result can be pasted into a post or document almost as is. On request, the model reshapes the output just as easily — from a checklist to a table, from a list to a short paragraph.
Examples prompts and responses
Below are real MiniMax M2.7 responses produced on Genosai. Prompts and text are shown unchanged.
Prompt: Suggest 3 ad headline options for an online personal-finance course. Keep them short.
MiniMax M2.7 response:
- "Master Your Money in 30 Days"
- "Start Building Wealth Today"
- "Smart Finance for Everyone"_Generated on Genosai.io with MiniMax M2.7._
The second example shows the model laying out a clear, structured checklist.
Prompt: Create a 5-step checklist for preparing a webinar announcement post.
MiniMax M2.7 response:
# 5-Step Checklist for Preparing a Webinar Announcement Post
## Step 1: Define Core Information
- [ ] Webinar title and topic
- [ ] Date and time (with timezone)
- [ ] Duration
- [ ] Target audience
## Step 2: Craft Compelling Content
- [ ] Hook/opening statement
- [ ] Key takeaways or agenda (3-5 points)
- [ ] Speaker credentials and photo
- [ ] Benefits for attendees
## Step 3: Add Visual & Technical Elements
- [ ] Eye-catching graphic or banner
- [ ] Logo/branding
- [ ] Registration/call-to-action button
- [ ] Link to registration page
## Step 4: Include Logistics
- [ ] Platform name (Zoom, Teams, etc.)
- [ ] Whether it's free or paid
- [ ] Capacity limits
- [ ] Post-event resource availability_Generated on Genosai.io with MiniMax M2.7._
How to use on Genosai
- Sign in to your Genosai account and open the text studio.
- In the model list, pick MiniMax M2.7 in the MiniMax section.
- Describe the task step by step and state the output format — a list, a checklist, several options.
- Enter your prompt: the more specific the input, the more precise the answer.
- Send the request and, if needed, ask for edits — shorter, an extra option, a different tone.
- Copy the finished text or keep the conversation going, building on previous messages.
Prompts
Suggest 5 ad headline options for [product], short and with a different angle each.Create a [N]-step checklist for [task] with checkboxes and short sub-points.Break the task [task] into a sequence of steps and describe what to do at each one.Write an announcement post for [event]: a catchy first paragraph, the benefit, and a call to action.Review this code snippet, find the bug, and propose a fix with comments: [paste code]Draft a week-long launch plan for [project]: tasks per day with owners and expected results.Summarize the text below as a bulleted list of key points: [paste text]Generation cost
On Genosai MiniMax M2.7 is billed by tokens — you pay for the actual size of the prompt and the answer, so a short question is cheaper than a long analysis. A typical request costs roughly 0.5 credits. The final amount depends on prompt length and answer size.
Starter credits after sign-up let you try MiniMax M2.7 for free, and top-ups work with local cards without a VPN. See current rates and balance on the Pricing page.
How it compares
MiniMax M2.7 is an inexpensive model that leans into agentic and creative tasks. If you want a larger multilingual model with strong coding, look at Qwen3.5 397B. For deep reasoning and a long context there is DeepSeek V3.2, for a balance of speed and volume GPT-5.4 Mini, and when top speed matters Gemini 3 Flash.
| Model | Context on Genosai | Cost per request | Strength |
|---|---|---|---|
| MiniMax M2.7 | 125,000 | 0.5 credits | Agentic and creative tasks |
| Qwen3.5 397B | 230,000 | 2 credits | Multilingual work and code |
| DeepSeek V3.2 | see the model page | — | Reasoning and long context |
| GPT-5.4 Mini | 380,000 | 2 credits | Speed and volume |
All models live in a single Genosai interface, so you can compare them on your own task and pick the best fit for price and quality.
Limitations and tips
MiniMax M2.7 is strong but not all-powerful. On Genosai it works with text only — there is no image or file processing here, so pick another catalog model for picture tasks. There is no built-in web search either: add fresh data from the web to your prompt yourself. In rare cases, in multilingual text the model may slip in a stray character; regenerate the answer or state the language explicitly in the prompt.
To get the best result, describe the task step by step and set the output format explicitly: a list, a checklist, a number of options. For agentic scenarios, phrase the instruction sequentially — the model holds such chains well when each step is stated on its own rather than packed into one long sentence. If an answer comes out generic, ask it to add specifics and examples; if you need a different tone, name it directly. It helps to state the count up front — "give me 5 headlines" rather than "give me headlines" — so the result is easier to pick from.
Keep the model's profile in mind too. MiniMax M2.7 is tuned for structure and action, so for long narrative text or subtle style it is worth reviewing the output and polishing by hand. And for complex multilingual or large long-context tasks, compare the result with Qwen3.5 397B — it holds more context and is stronger at translation.
FAQ
What is MiniMax M2.7 and who built it?
MiniMax M2.7 is a text model from MiniMax, released on March 18, 2026. It uses a Mixture-of-Experts design with 230 billion parameters, of which about 10 billion are active per token. On Genosai it is available online with no separate subscription.
What context length does MiniMax M2.7 support on Genosai?
On Genosai the model works with a 125,000-token context. That is enough for long conversations, large briefs, and big documents. The whole text fits in one window without splitting it into chunks.
What tasks is MiniMax M2.7 good for?
The model is tuned for agentic workflows, tool use, and multi-step tasks, as well as creative content like headlines, checklists, and posts. On benchmarks it holds 97% instruction adherence across 40+ complex skills.
How much does a MiniMax M2.7 request cost?
A single MiniMax M2.7 request on Genosai costs 0.5 credits — one of the most affordable models in the catalog. You pay for actual generations with no monthly subscription. Credits can be topped up whenever you need them.
Can MiniMax M2.7 work with files on Genosai?
No. On Genosai, MiniMax M2.7 is available as a text model and processes text only. For image and document tasks, pick a model with file support from the catalog.
Do I need a subscription to use MiniMax M2.7?
No. Genosai gives you access to MiniMax M2.7 right in the browser — no MiniMax account, API keys, or setup. Just sign in to Genosai and pick the model in the text studio.