productivity hack with Grok-3 & Gamma

Alibaba's QwQ model, MCP got easier for AI Agents, Grok-3+Gamma

Author

Martin Musiol
March 08, 2025 • Estimated Reading Time: 5 minutes

Hey ,

2025 is the year of AI agents. And as they are powered by LLMs, the better LLMs do the better are the agents. It is about their performance, but also features like context window length, latency, and hallucination rates.

Today on the docket:

  • LLMs: Alibaba’s new QwQ-32B establishes new standards

  • AI Agents: coding agent in Cursor connects to data efficiently via MCP servers (Anthropic’s protocol), with Composio streamlining the process.

  • And at the bottom our productivity hack for creating killer slides fast. ⬇️⬇️

Alibaba’s QwQ-32B establishes new standards for AI models

The Chinese company Alibaba has released a reasoning LLM with the slightly cryptic name QwQ-32B. The latter part stands for its number of parameters: 32 billion. For comparison DeepSeek-R1 has 671 billion (20x).

This is matters a big deal, because the more parameters the higher compute costs and latency.

This relatively small model outperforms very large models significantly in math (AIME benchmark). It is ahead of R1, and OAI’s o1.

A horizontal bar chart titled “AIME 2024 (Competition Math),” comparing performance scores (percentages) of various large language models (LLMs). The chart is sorted from highest to lowest scores. OpenAI’s “o3-mini (high)” leads at 86%, followed by Alibaba’s QwQ-32B at 78%, OpenAI’s “o1” at 72%, and DeepSeek R1 at 68% (highlighted with a purple arrow). Other models shown include Claude 3.7, Gemini Pro, Gemini 2.0 Flash, Llama 3.3 70B, DeepSeek V3, Claude Sonnet, Qwen2.5 Max, Llama 3.1, GPT-4o mini, and several others with lower performance scores down to Claude 3.5 Haiku at 3%.

In other benchmarks it performs great as well.

It is open source: download it and work with it (65GB) here:

With QwQ, we see another 90% price cut in word generation.

Meanwhile at Meta

Llama 4 was set to be released in January but R1 made them to rethink/ rework their model.

A screenshot of a Reddit discussion from the subreddit r/LocalLLaMA. The original post asks, “Where is Llama 4? I expected that in January,” followed by a discussion tag and some additional commentary noting Meta’s recent inactivity compared to other labs. Below, users speculate about the delay, suggesting that Meta might have been dissatisfied with DeepSeek R1 outperforming their anticipated Llama 4 model, leading to internal discussions and significant strategy changes. Another commenter adds rumors about Mark Zuckerberg (“zuck”) creating internal discussions (“war rooms”) in response to DeepSeek’s performance, suggesting that higher-ups at Meta were concerned about competitive losses. The commenter predicts Meta might skip directly to labeling their next release “Llama 5” instead.

With Llama 4 they have to release something stronger than QwQ-32b. That’s a must. But in the meantime DeepSeek announced that R2 is coming in May 2025. 🙈

Turbulent times ahead, but all good for the consumer side of it.

It’ll be cheaper and more performant.

Composio supports MCP now

When working with tools like Cursor AI, Windsurf AI, or Anthropic you want to connect it reliably to various data. MCP is a protocol to streamline that process.

You no longer have to struggle with setting up MCP servers or worry about server reliability, availability, and authentication complexity.

Composio has built the largest source of fully managed MCP servers, with complete auth support.

What they have to offer

  • Fully managed MCP servers for 100+ apps like Linear, Slack, Notion, Calendly, etc.

  • Managed Auth (OAuth, ApiKey, Basic) for applications

  • Improved tool calling accuracy

That is a big deal, as it saves a lot of time.

Productivity hack with Grok-3 & Gamma

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