MiniMax M1 is described by its maker as the world's first open-weight, large-scale hybrid-attention reasoning model, featuring 456 billion total parameters with 45.9 billion activated per token. Released in June 2025 under the Apache 2.0 license, it pairs a 1M-token context window with a hybrid Mixture-of-Experts architecture and a Lightning Attention mechanism. The model scores 56.0% on SWE-bench (software engineering) and 86.0% on AIME 2024 (mathematics), and leads open-weight models on tool-use benchmarks such as TAU-bench. At 80K-token reasoning lengths, Lightning Attention uses roughly 30% of the compute that DeepSeek R1 requires, enabling efficient scaling of test-time compute across deep reasoning and long-context tasks. The 80K variant provides an 80,000-token reasoning budget for extended thinking. MiniMax trained M1 with CISPO, a reinforcement learning algorithm it reports converges about twice as fast as alternatives, completing training in three weeks on 512 H800 GPUs.
MiniMax M1 runs on 1 route through the qynio gateway. Compare residency, zero retention, and training posture at a glance β full data-handling detail per route below.
| Provider | Region | Zero data retention | Training | Input | Output |
|---|---|---|---|---|---|
| US | Zero data retention | No | $0.55 | $2.20 |
MiniMax M1 runs on a single route through the qynio gateway today, so its availability is that provider's availability.
Name a second model in the same request and the gateway tries it on retriable errors, so a busy hour never has to reach your users. .
Measured over the last 30 days from each provider's official status feed via StatusGator. Refreshed hourly. See uptime for every provider qynio monitors.
Each route hosting MiniMax M1 has its own privacy posture, residency, and no-KYC terms. Postures are maintained by qynio with a last-verification timestamp.
Zero data retention is on by default on Pay-as-you-go β no action required. No training on customer data. US; wallets; deposit available.
Independent benchmark scores β composite indices for reasoning, coding, and math, plus individual eval scores where available.
Call MiniMax M1 through the qynio gateway with one API key. Let your coding agent set it up, or call it directly β qynio is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.
Copy this and paste it into a coding agent like Claude Code, Cursor or Codex and it'll wire up qynio for you.
import OpenAI from "openai";const client = new OpenAI({apiKey: process.env.QYN_API_KEY,baseURL: "https://api.qyn.io/v3/compat",});const completion = await client.chat.completions.create({model: "novita/minimaxai/minimax-m1-80k",messages: [{ role: "user", content: "Hello" }],});console.log(completion.choices[0].message.content);
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