AI & LLMs
Mistral Large 4 launches with 1.05T parameters
Mistral Large 4 is a 1.05T-parameter open-weight MoE model with a 1M-token context, in API preview at $1.36 per million input tokens. Weights follow in October.
Moe news and analysis
Mixture-of-experts (MoE) models, which hold many parameters but activate only a small share for each token, so they run cheaper than their size suggests: GLM, Qwen and Granite releases. Each story gives the total and active parameter counts, license, hardware needed and hosted price.
AI & LLMs
Reflection AI launches Beam, a 501B open-weight model
Reflection AI's Beam has 501B parameters but uses 23B per token, scores 80.9 on SWE-Bench Verified, and ships weights under Apache 2.0 later in October.
AI & LLMs
Aleph Alpha Kolibri 1: open German-English MoE model
Aleph Alpha released Kolibri 1 on October 3: a 78.1B-parameter open model with 3.46B active, built for German and English, under the Apache 2.0 license.
AI & LLMs
Xiaomi MiMo-V2.6-Pro ships 1T open weights under MIT
Xiaomi's MiMo-V2.6-Pro has 1.02 trillion parameters, 42 billion active, a 1M-token context and MIT-licensed weights, but needs about 680 GB of GPU memory.
AI & LLMs
Qwen3.8-Omni-Flash cuts audio input costs by 98%
Alibaba's new omnimodal model reads text, images, audio and video inside a 1M-token context, and prices audio input more than 98% below its predecessor.
AI & LLMs
GLM-5.3 weights ship under a custom license and need eight GPUs
Z.ai's flagship GLM-5.3 weights are on Hugging Face after a safety review delay. The license is not MIT, and the model needs at least eight high-end GPUs.
AI & LLMs
Qwen3.8-Flash-Next holds 125B parameters but runs only 6B
Alibaba released Qwen3.8-Flash-Next on August 26, 2026. It activates 6B of 125B parameters per token, costs $0.16 per million input tokens, and previews Qwen4.
AI & LLMs
Z.ai and IBM ship open-weight reasoning models a day apart
Z.ai released GLM-5.3-Flash under MIT with 320B parameters. IBM released Granite 4.2 under Apache 2.0 at 3B to 30B. They suit very different hardware.
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