I cut my OpenClaw cost by 95%

An open source model just released that is: Better than Opus 4.6 for coding Faster than Sonnet State of the art for tool calling Minimax just dropped M2.5. It scores on par with Opus 4.6 on coding benchmarks. It's built from the ground up for agentic workflows. And it costs a fraction of what you'd pay for frontier models. We're talking about a 95% reduction in cost. I've already switched my entire OpenClaw setup to run on it. Let me show you exactly why, and how you can do the same. Why Minimax M2.5 Changes the Game Here's the problem with running AI agents today. Frontier models like Opus 4.6 are incredibly capable, but they're also incredibly expensive. If you want an agent that runs autonomously for hours, handling complex multi-step tasks, your API bill adds up fast. @MiniMax_AI M2.5 solves this problem entirely. It hits 80.2% on SWE-Bench Verified, which puts it right alongside Opus 4.6 in coding performance. It scores 76.3% on BrowseComp for search tasks and 76.8% on BFCL for agentic tool-calling. What really stands out is that it's designed for long-horizon agentic tasks. This means your OpenClaw agent can independently keep running, planning, and finishing complex tasks without falling apart midway. The model doesn't lose context. It doesn't get confused 15 steps into a workflow. At roughly $1 per hour with 100 tokens per second, you can now scale long-running agents in a way that was never economically feasible before. And here's what most people miss. M2.5 only activates 10 billion parameters. That makes it the smallest among all Tier-1 models. So if you're self-hosting, you get an unparalleled advantage in terms of compute and memory requirements. I'm not saying it's better than Opus 4.6 at everything. But for agentic coding and automation workflows? It's the better choice at a fraction of the cost. How to Set Up OpenClaw with Minimax M2.5 The setup is straightforward, and here's the step-by-step walkthrough. Step 1: Install OpenClaw Follow the on-screen instructions. The installer handles everything. Note: Installation commands may vary by OS. Always grab the latest command from the official site: openclaw.ai Step 2: Pick Your Model During setup, OpenClaw will prompt you to choose a model. Select Minimax M2.5. It's the recommended choice. Step 3: Setup OAuth or get your API key Subscribe to a coding plan here: https://platform.minimax.io/subscribe/coding-plan Minimax offers a starter Coding Plan at $8.8/month, which gives you production-grade agentic coding accessible to individual developers. Step 4: Register Your Telegram Bot To create your bot: Open Telegram Search for Botfather Start a chat and choose Create New Bot Assign a name and a unique username BotFather will create the bot instantly. Step 5: Copy the Bot Token After creating the bot, BotFather will provide a Bot Token. Copy this token, you'll paste it into your terminal when ClawdBot asks for it during channel setup. After the setup, you can access it Telegram, see how I am able chat with my new agent name Gilfoyle (yes the one from Silicon valley..xD) 👇 And that's all. You can take it from here. What I'm Actually Building With This I don't just run one agent. I run three. Think of them as AI employees that work for me around the clock. Each one has a specific role, and I interact with all of them through Telegram. Neo: My AI Engineer Neo is a highly capable software developer that works 24/7. Whether it's building a feature, fixing a bug, or automating some tedious workflow, I just message Neo and it gets done. Because M2.5 excels at long-horizon tasks, Neo can take a complex coding assignment and work through it independently. It plans, writes code, tests, and iterates without me having to babysit every step. Pulse: My Deep Researcher Every morning at 8:30 AM, I get a curated research briefing from Pulse. It scans the sources that matter most: Hugging Face blog and trending models Trending GitHub repos Official blogs from major AI labs Relevant subreddits Then it distills everything into a clean, actionable summary. No noise, no scrolling through 47 tabs, just the signal that actually matters. This alone has saved me hours every week. I stay on top of what's happening in AI and ML without the information overload. Pixel: My Graphic Designer Pixel understands the Daily Dose of Data Science brand. It creates educational visuals that have our signature hand-thrown feel. It breaks down complex concepts into simple illustrations. And it keeps everything on-brand and consistent across all our content. When I need a visual for a newsletter or social post, I message Pixel with the concept. It delivers something that looks like it came from our design team. All three agents run on Minimax M2.5, available to me through Telegram, at a fraction of what I'd pay with frontier models. If you want to see the full setup in action, I published a 30-minute YouTube masterclass on OpenClaw where you learn how to create your first agent and then scale from 1 to 10 so they can all collaborate and work 24/7 for you. I started with Minimax M2.1, switched to Opus 4.6 for better results, and now I've been getting consistently strong results with M2.5. Will continue testing and sharing what we find. Check this out: https://youtu.be/aFQJYaornJ4 Stay tuned, I'll be covering more on deploying OpenClaw securely and how you can also optimize the token usage. If you found it insightful, reshare with your network. Find me → @akshay_pachaar ✔️ For more insights and tutorials on LLMs, AI Agents, and Machine Learning!