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MiniMax 2.7: GLM-5 at 1/3 cost SOTA Open Model

By PulseAugur Editorial · Summary by None from 4 sources

MiniMax has released MiniMax 2.7, an open-source model that matches the performance of Z.ai's GLM-5 on several benchmarks but at a significantly lower cost. The model is noted for its efficiency and claims to be the first to deeply participate in its own evolution, handling a portion of its workflow. MiniMax is also exploring multi-agent collaboration and finance use cases, alongside releasing an open-source demo for entertainment applications called OpenRoom. AI

Summary written by None from 4 sources. How we write summaries →

RANK_REASON New model release from a significant Chinese AI lab matching SOTA open model performance at lower cost.

Read on Smol AINews →

MiniMax 2.7: GLM-5 at 1/3 cost SOTA Open Model

COVERAGE [4]

  1. Smol AINews TIER_1 (CA) ·

    MiniMax 2.7: GLM-5 at 1/3 cost SOTA Open Model

    **MiniMax M2.7** is the headline model release, described as a "self-evolving agent" with strong performance metrics including **56.22% on SWE-Pro**, **57.0% on Terminal Bench 2**, and parity with **Sonnet 4.6**. It features recursive self-improvement in skills, memory, and archi…

  2. Smol AINews TIER_1 ·

    Z.ai GLM-5: New SOTA Open Weights LLM

    **Zhipu AI** launched **GLM-5**, an **Opus-class** model scaling from **355B to 744B parameters** with **DeepSeek Sparse Attention** integration for cost-efficient long-context serving. GLM-5 achieves **SOTA on BrowseComp** and leads on **Vending Bench 2**, focusing on office pro…

  3. Smol AINews TIER_1 Nederlands(NL) ·

    GLM-4.5: Deeper, Headier, & better than Kimi/Qwen/DeepSeek (SOTA China LLM?)

    **Z.ai** (Zhipu AI) released the **GLM-4.5-355B-A32B** and **GLM-4.5-Air-106B-A12B** open weights models, claiming state-of-the-art performance competitive with **Claude 4 Opus**, **Grok 4**, and OpenAI's **o3**. These models emphasize token efficiency and efficient reinforcement…

  4. dev.to — LLM tag TIER_1 · RunC.AI Offical ·

    SGLang vs vLLM: Which LLM Serving Framework Should You Use?

    <p><em>Originally published at <a href="https://blog.runc.ai/sglang-vs-vllm/" rel="noopener noreferrer">https://blog.runc.ai/sglang-vs-vllm/</a>.</em></p> <h2 id="key-takeaways">Key Takeaways</h2> <ul> <li> <code>vLLM</code> is still the default starting point for many teams beca…

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