Playground first · official relay route · editorial benchmark read
Play MiniMax M3 online
MiniMax M3 Online helps you decide if MiniMax M3 belongs in your workflow. Open the Playground, run a long page, then move to the official API relay path.
1M
context window
59.0%
SWE-Bench Pro
100T
multimodal training tokens
9x+
prefilling speedup
MiniMax M3 Playground
Drop a URL or prompt. Run the workflow.
Breakthroughs and advantages
MiniMax M3 breaks out across memory, coding, multimodal scale, and runtime.
MiniMax M3 is strongest when the buyer separates the 1M context story, coding benchmark story, multimodal story, and acceleration story instead of reading one generic block of AI copy.
Context ceiling
1M
MiniMax M3 can stay inside a large working set.
MiniMax M3 is interesting when the session is too large for a short demo prompt: long specs, repo notes, procurement pages, product docs, and extended review chains.
Coding benchmark
59.0%
MiniMax M3 keeps the conversation tied to software work.
The SWE-Bench Pro number matters because it pushes MiniMax M3 out of generic model marketing and back into actual engineering evaluation.
Multimodal scale
100T
MiniMax M3 is framed as native multimodal, not patched-on vision.
That matters when screenshots, UI states, tables, and long text all have to stay in one reasoning loop instead of being split across separate tools.
Speed profile
MSA
MiniMax M3 is also a latency story.
MiniMax Sparse Attention and the reported 9x+ prefilling plus 15x+ decoding gains are what make a large context window operational instead of decorative.
1M context window
MiniMax M3 reported signal
1M
The main infrastructure jump behind long document, long codebase, and long video understanding.
SWE-Bench Pro
MiniMax M3 reported signal
59.0%
MiniMax positions MiniMax M3 in the frontier coding tier rather than in a generic assistant tier.
Prefilling acceleration
MiniMax M3 reported signal
9x+
A long context number only matters if the input stage remains usable during real sessions.
Decoding acceleration
MiniMax M3 reported signal
15x+
MiniMax says MiniMax M3 keeps decoding practical enough for longer agent loops and iterative coding runs.
Autonomous engineering run
MiniMax M3 reported signal
24h
The notable point is not just output quality but MiniMax M3 continuing through repeated tool calls and benchmark submissions.
Hopper FP8 utilization
MiniMax M3 reported signal
71.3%
In MiniMax-reported internal CUDA optimization work, the model pushed hardware utilization from 7.6% to 71.3%.
MiniMax family comparison
MiniMax M3 versus the rest of the MiniMax line.
MiniMax M3 is where the MiniMax line brings frontier coding, native multimodal input, and a 1M context window into one model. Earlier generations serve different purchase questions.
Reading tip
Use the table to decide whether MiniMax M3 is the right product entry. If you need long context and multimodal workflow evaluation, MiniMax M3 should lead.
| Model | Best fit | Context frame | Evidence |
|---|---|---|---|
MiniMax M3 lead modelJune 2026 Combines frontier coding, native multimodal input, and MiniMax Sparse Attention in one release. | Frontier long-context coding plus native multimodal | 1M window | 59.0% SWE-Bench Pro, 66.0 Terminal-Bench 2.1, 24h autonomous engineering run, 9x+ prefilling and 15x+ decoding acceleration. |
MiniMax M2.7 March 2026 Focused on complex agent harnesses, Office workflows, skill adherence, and model self-improvement loops. | Self-evolving agent harness and complex productivity work | Not the headline | 56.22% SWE-Pro, 57.0 Terminal Bench 2, GDPval-AA ELO 1495, 97% skill adherence across 40 complex skills. |
MiniMax M2.5 February 2026 Optimized for coding, agentic tool use, search, and office tasks with a speed and cost emphasis. | High-throughput coding, search, and tool use for real-world productivity | Production-speed focus | 80.2% SWE-Bench Verified, 51.3% Multi-SWE-Bench, 76.3% BrowseComp, 37% faster on SWE-Bench Verified than M2.1. |
MiniMax M2 October 2025 Built around planning, tool use, deep search, and a better balance of price, speed, and practical agent performance. | Born for agents and code | Agent-first base generation | Open-sourced as the agent-oriented base model, positioned near top overseas models on tool use and deep search while being faster and cheaper. |
MiniMax M3 versus other brands
MiniMax M3 enters the frontier tier against closed-model references.
This is a buying frame, not a benchmark leaderboard. MiniMax M3 is positioned against Claude Opus 4.7, GPT-5.5, and Gemini 3.1 Pro while keeping an open deployment story.
MiniMax M3
MiniMax says M3 beats GPT-5.5 and Gemini 3.1 Pro on SWE-Bench Pro and approaches Claude Opus 4.7.
Comparative read
Native multimodal plus 1M context plus open deployment is the main reason M3 changes the buying conversation.
Claude Opus 4.7
Anthropic positions Opus 4.7 as a frontier model for coding and AI agents with a 1M context window.
Comparative read
Opus is the closed-model reference MiniMax M3 is chasing most closely in coding and long-running agent work.
GPT-5.5
OpenAI positions GPT-5.5 for coding and professional work with a 1,050,000 context window in the API.
Comparative read
GPT-5.5 remains a major closed-model reference, but MiniMax M3 is framed as the open-weight push into that tier.
Gemini 3.1 Pro
Google positions Gemini 3.1 Pro as advanced intelligence with complex problem-solving and strong agentic and coding capability.
Comparative read
Gemini is the multimodal and reasoning reference on the closed side that MiniMax M3 is explicitly compared against in the collected materials.
Application scenarios
Where MiniMax M3 becomes operational, not decorative.
MiniMax M3 keeps showing up in long code review, long document analysis, visual reasoning, and repeated tool execution. That is why this site puts the Playground front and center — test the model before you read the pricing page.
Long code and repo review
MiniMax M3 fits sessions where too much state has to stay live at once.
Common patterns include reading a large codebase, comparing multiple specs, following issue history, reviewing logs, and carrying architectural constraints across a long edit loop.
Web research and structured extraction
MiniMax M3 works well when the output has to be organized instead of merely answered.
That includes long product pages, documentation sets, token-plan pages, competitive research, procurement pages, and research notes that need to be turned into structured summaries and signals.
Visual plus text reasoning
MiniMax M3 is more useful when screenshots, diagrams, tables, and long text have to stay in one run.
Generalized from the collected examples, this covers UI recreation from references, document understanding with figures, page QA, and mixed-media analysis where text-only models lose too much context.
Long video and meeting digestion
MiniMax M3 is positioned for tasks where the raw asset is too large to summarize manually first.
A common pattern is turning long talks, demos, or internal recordings into chaptered reports, screenshots, narrative summaries, and reusable notes without first reducing everything to a short transcript.
Agentic workflow execution
MiniMax M3 is built for tasks that need planning, tool use, correction, and persistence.
Across the material, the shared story is not just single-turn code generation. It is multi-step execution: searching, validating, revising, calling tools, and continuing past early plateau points.
Office and deliverable work
MiniMax M3 also inherits a productivity direction from the MiniMax line.
Stripping away the one-off examples, the common use cases are report drafting, slide support, spreadsheet reasoning, high-fidelity editing, and document transformation across repeated review rounds.
Reference surfaces
Source signals worth checking.
Three independent sources — a major tech publication, a hands-on developer review, and an open-source community thread — each confirming the MiniMax M3 performance story from a different angle.
VentureBeat: MiniMax M3 eclipses GPT-5.5 on key benchmarks at 5–10% of the cost
VentureBeat reports that MiniMax M3 surpasses GPT-5.5 and Gemini 3.1 Pro on SWE-Bench Pro while costing a fraction of competing frontier models. The article covers benchmark methodology, pricing comparison, and market positioning.
Thomas Wiegold: MiniMax M3 matches GPT-5.5 and Opus on real coding tasks
An independent developer puts M3 through real coding tests — not benchmark slides. The review covers code generation quality, reasoning depth, and how M3 compares to GPT-5.5 and Claude Opus in day-to-day development workflows.
r/LocalLLaMA: developers vet MiniMax M3's 1M context and coding claims
Hundreds of open-source developers on r/LocalLLaMA discuss M3's real-world performance: the 1M context window, open-weight deployment, coding benchmark scores, and whether the multimodal claims hold up outside of marketing materials.
Video briefings
See MiniMax M3 in motion — benchmarks, coding, and product strategy.
These English videos show MiniMax M3 under coding pressure, agent pressure, and broader product positioning — turning benchmark and workflow stories into motion.
MiniMax M3 hands-on benchmark briefing
English explainer focused on coding relevance, long-context positioning, and why MiniMax M3 drew immediate attention.
Watch on YouTubeMiniMax M3 with Hermes Agent
English walkthrough that places MiniMax M3 inside a practical agent workflow instead of stopping at benchmark slides.
Watch on YouTubeMiniMax M3 tested on real projects
English project-based review that is useful for visitors who want to see MiniMax M3 under implementation pressure.
Watch on YouTubeFAQ
Frequently asked questions about MiniMax M3 Online.
What is MiniMax M3 Online?
MiniMax M3 Online gives you a free Playground to try every MiniMax model — M3, M2.7, M2.5, and M2. Drop a URL, inspect structured output, and decide if MiniMax fits your workflow. When you're ready, the API page has everything you need to go from testing to production.
Why lead with a Playground instead of a pricing table?
Because the first decision is capability, not cost. Drop a hard URL into the Playground, inspect the extracted structure, and see whether MiniMax M3 handles coding, agentic, and multimodal operations. The pricing page is one click away when you need it.
What makes MiniMax M3 different from generic model landing pages?
MiniMax M3 combines three signals rarely shipped together in open-weight launches: frontier coding, a 1M context window, and native multimodal training. This site keeps those operational metrics visible instead of vague AI copy.
Can I try all MiniMax models for free?
Yes. The Playground gives you free access to MiniMax M3, M2.7, M2.5, and M2. Test long-context analysis, coding, and multimodal tasks directly in the browser before deciding which model fits your stack.
What does the API page cover?
The API page covers Token Plans, Subscription Keys, integration docs, rate limits, and the full path from Playground testing to production relay access. Everything a buyer needs to move from trial to deployment.
Final call
Try the Playground, then explore the API.
MiniMax M3 stays centered on one keyword cluster and one user action: a stronger reading surface and a clearer test surface. That is what this homepage delivers.