MiniMax M3
MiniMax M3 is a 428B-parameter Mixture-of-Experts large language model from Shanghai-based MiniMax (稀宇科技), activating 22B parameters per token. It is the first open-weight model to combine frontier-level coding, a 1M-token context window, and native multimodal input in a single architecture.
Released June 1, 2026, M3 introduces MSA (MiniMax Sparse Attention), a sparse attention mechanism that cuts per-token compute at one-million-token context to 1/20th of its predecessor M2.7. On SWE-Bench Pro it scores 59.0%, edging past GPT-5.5 (58.6%) and Gemini 3.1 Pro, with weights open-sourced on Hugging Face shortly after API launch.
Think of MSA as a librarian who scans the index before pulling shelves — skipping 95% of stacks to fetch only the relevant pages.
Search Interest
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Nascent0–7 days
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Emergent ← now8–30 days
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Validating31–90 days
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Rising91–180 days
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Established180 days +
Why is it emerging now?
MiniMax M3 landed June 1 as the first open-weight model pairing frontier coding (59.0% SWE-Bench Pro) with a true 1M-token context and native multimodal input — all at $0.30/M input tokens, roughly 15x cheaper than Claude Opus 4.7. The weights followed on Hugging Face by June 13, removing the last barrier for self-hosted deployment.
Outlook
6-month signal projection and commercial timeline.
Open weights plus 15x cost advantage over Claude Opus 4.7 make M3 the default open-weight baseline for long-context agentic coding through Q3 2026.
Risk · Benchmark self-reporting without independent replication; DeepSWE leaderboard omission leaves credibility gap.
Analogs · deepseek-v3 · kimi-k2-6 · qwen3
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nowAPI live, weights public
MiniMax API and OpenRouter both live; weights on Hugging Face enable self-hosted deployments.
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3-6moComparison and fine-tuning tools
Benchmark comparison sites and LoRA fine-tuning services targeting the 22B-active parameter sweet spot.
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6-12moEnterprise long-context plays
1M-context codebase analysis and document-processing SaaS built on M3 or its successors.
Competition & Opportunity for term “MiniMax M3”
Three heuristic signals derived from the tracked queries, the term's monetization cards, and its cluster neighbors. Directional, not audited.
Ideas for term “MiniMax M3”
Buildable pitches — turn this term into an article, site, product, post, newsletter, video, or course. Steal any card and run with it.
High-intent comparison query with no authoritative benchmark roundup yet. Cover SWE-Bench Pro, BrowseComp, pricing, and context window side by side.
428B MoE weights create concrete deployment questions. Tutorial gap is real — only a handful of posts exist in the first two weeks.
Technical explainer for the architecture innovation behind M3's efficiency claims — underserved despite being the core differentiator.
Category comparison anchored on the Chinese open-weight wave — high-volume query with fragmented coverage.
Legal, finance, and medical teams processing 500-page documents need long-context models; M3's $0.60/M token standard rate enables viable unit economics.
128-expert MoE supports LoRA on 22B activated parameters. Service targeting teams wanting M3-class performance on proprietary codebases.
Head-to-head with real codebases beats benchmark screenshots; 20-30 minute format with live screen capture is currently undersupplied.
Four Chinese labs released frontier open-weight coding models in April 2026. Then MiniMax showed up in June and reset the benchmark.
Most 'million-token' models struggle past 200K in practice. M3's MSA architecture makes a different bet — and the inference speed numbers back it up.
MiniMax listed on the Hong Kong Stock Exchange on January 9, 2026 — and six months later released a model that outscores GPT-5.5 on SWE-Bench Pro for a fraction of the price.
What People Search
Long-tail queries from Google Suggest + Trends. Volume and competition are heuristics — directional, not audited. Content Type comes from query shape.
SERP of term “MiniMax M3”
What searchers see today — organic results on top, paid ads if anyone's bidding. Ad density is a real-time commercial signal.
FAQ
What is MiniMax M3?
MiniMax M3 is a 428B-parameter Mixture-of-Experts large language model from Shanghai-based MiniMax (稀宇科技), activating 22B parameters per token.
Why is MiniMax M3 emerging now?
MiniMax M3 landed June 1 as the first open-weight model pairing frontier coding (59.0% SWE-Bench Pro) with a true 1M-token context and native multimodal input — all at $0.30/M input tokens, roughly 15x cheaper than Claude Opus 4.7. The weights followed on Hugging Face by June 13, removing the last barrier for self-hosted deployment.
When did MiniMax M3 emerge?
Publicly emerged around 2026-06-01 (about 13 days ago as of 2026-06-14). EarlyTerms first recorded a pipeline signal on 2026-06-01.
Related Terms
Other terms in the same space — aliases, subtypes, competitors, and neighbors to explore next.
- Competitor deepseek-v4 DeepSeek V4 is a series of open-weight Mixture-of-Experts language models from DeepSeek that bring one-million-token context to… →
- Competitor kimi-k2-6 Kimi K2.6 is Moonshot AI's April 20, 2026 open-weight flagship — a 1T-parameter Mixture-of-Experts model (32B active, 384 experts, 256K… →
- Competitor glm-5-1 GLM-5.1 is Z.ai's 754-billion-parameter open-weight large language model, purpose-built for agentic engineering and long-horizon coding… →
- Competitor mimo-code MiMo Code is an open-source, terminal-native AI coding agent from Xiaomi's MiMo team, built to sustain decision quality across hundreds… →
- Related agentic-coding Agentic coding is the software-development pattern where an autonomous AI agent plans, writes, tests, and iterates on code against a… →
- Related context-window A context window is the span of tokens an LLM reads and reasons over in a single forward pass. →
- Related managed-agents Managed Agents is an infrastructure paradigm where cloud platforms host, orchestrate, and operate AI agents as a service. →
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Sources
Primary URLs this report cites — open any to verify the claim yourself.
- 01 MiniMax M3 — Hugging Face model card (428B MoE, 22B active, MSA, 1M context) huggingface.co ↗
- 02 MarkTechPost — MiniMax M3 launch coverage (Jun 1, 2026) marktechpost.com ↗
- 03 NVIDIA Developer Blog — MiniMax M3 deployment guide developer.nvidia.com ↗
- 04 The Decoder — Open-weight 1M-context model analysis the-decoder.com ↗
- 05 Artificial Analysis — M3 benchmark review and caveats artificialanalysis.ai ↗
- 06 Wikipedia — MiniMax Group (company background, HK IPO Jan 2026) en.wikipedia.org ↗
- 07 GitHub — MiniMax-AI/MiniMax-M3 (official repo, created Jun 1 2026) github.com ↗