MiniMax M3

Headlines · 5

1. Oct 22
   MiniMax Shares Fall Below IPO Price After Post-Listing Rally

   MiniMax shares fell as low as HK$159.3 during intraday trading on October 22, below the HK$165 IPO offering price, according to IT之家. The stock had reached HK$1,330 in March, more than seven times its offering price, before the post-listing rally reversed. 虎嗅 AI commentary attributes the pressure to competition, commercialization challenges and a lower-margin shift toward business customers.

   IT之家 AI · 🔥 0
2. Oct 20
   MiniMax M3.1 Flash benchmark gains spark training-data allegations

   MiniMax M3.1 Flash earned an Artificial Analysis Intelligence Index score of 42, 13 points above M3, but researchers questioned whether the gain reflected genuine capability or memorized benchmark questions. Researcher Binkg reported that the model retained the original answer after a public AA-Omniscience question was modified, and TMTPost reproduced a similar English-language failure, although the model answered correctly in Chinese. MiniMax opened the model weights on October 23, enabling independent testing, but no request logs or training records show that the company accessed or used private evaluation questions.

   cnBeta · 🔥 0
3. Oct 19
   SGLang adds Low-Latency Mode with plugin kernels for NVIDIA and AMD GPUs

   The SGLang, NVIDIA and AMD teams introduced SGLang Low-Latency Mode, which brings specialized low-latency kernels into the SGLang serving stack through a plugin framework, with NVIDIA kernels in sgl-nvidia-mega and AMD kernels in sgl-amd-mono. In AgentX trace replay with DeepSeek-V4.1-Flash with DSpark, the teams report P90 per-user token generation rising from 671.2 to 928.4 tokens/s (1.38x) on four NVIDIA GB300 GPUs at one concurrent session, and from 331.6 to 516.0 tokens/s (1.56x) on four AMD MI355X GPUs at four concurrent sessions, each against the SGLang baseline on the same hardware. The NVIDIA plugin also improved per-user decode speed by 12-38% at 1-8 concurrent requests on an 8K-input / 1K-output workload, and the teams say megakernel work is underway for GLM-5.3, K3 and MiniMax M3.

   LMSYS Blog · 🔥 0
4. Oct 19
   Tencent reportedly tests “Dongleya” AI learning community

   IT之家 reported, citing user feedback, that Tencent is beta-testing “懂了鸭,” an AI interactive-content community for children and teenagers. The website and WeChat mini program reportedly offer limited testing to parents with children and frontline teachers. Its built-in AI agents can reportedly turn natural-language prompts into 3D demonstrations, dynamic lessons, interactive picture books, lightweight games and memory cards without requiring programming skills. Users can browse community works and adapt others’ creations. IT之家 also said the model list includes DeepSeek-V4.1-Flash, DeepSeek V4 Pro, DeepSeek V4 Flash, Hy3, Hy4 preview, MiniMax M3, Kimi K3 and GLM-5.3. The supplied reports do not include direct confirmation from Tencent, and they describe the test’s access arrangements differently.

   DoNews · 🔥 0
5. Oct 9
   vLLM adds day-0 support for NVIDIA Vera Rubin NVL72, claims 7.8x throughput over GB200

   vLLM says it now runs on NVIDIA's Vera Rubin NVL72, with nightly CUDA 13.4 and PyTorch 2.15 container images and support for models from DeepSeek, Moonshot AI's Kimi, Z.ai's GLM and MiniMax. Working with NVIDIA, Red Hat and Inferact, the project reports early results of 7.8x throughput per GPU versus GB200 NVL72 on AgentX at matched interactivity and up to 3.7x higher VLM throughput versus GB300 NVL72 in MLPerf; these are its own early figures. MiniMax separately said its M3 model is now running on Rubin with vLLM, crediting the same collaborators.

   vLLM Blog · 🔥 0

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