Releases·Model Release
IQuest releases IQuest-Q1, a 320B-parameter MoE model for agentic coding and tool use
IQuest released IQuest-Q1 on Hugging Face, a Mixture-of-Experts model targeting agentic coding, reasoning, and multi-step tool use. The model has roughly 320B total parameters with an estimated 15B activated per token, making it a sparse MoE design aimed at efficient inference for agent workloads.
70 engagement1 sourceTue, Sep 29, 2026, 10:24 AM
AI Overview
- IQuest's IQuest-Q1 is a Mixture-of-Experts model with ~320B total parameters and ~15B activated per token, targeting agentic coding, reasoning, and multi-step tool use
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Releases·Model Release
Meta releases MobileMoE on-device MoE LLMs with sub-billion active parameters
Meta released MobileMoE, a family of on-device Mixture-of-Experts language models with sub-billion active parameters, aiming to improve the quality-efficiency trade-off for mobile LLMs. The family includes three scales (S/M/L) with 0.3B/0.5B/0.9B active parameters, each available in Base, SFT, and QAT variants.
Meta released MobileMoE, a family of on-device Mixture-of-Experts language models with sub-billion active parameters, aiming to improve the quality-efficiency trade-off for mobile LLMs. The family includes three scales (S/M/L) with 0.3B/0.5B/0.9B active parameters, each available in Base, SFT, and QAT variants.
58 engagement1 sourceredditMon, Aug 24, 2026, 06:49 PM
Releases·Model Release
Tencent Hy Team releases Hy3, a 295B-parameter MoE model
Tencent's Hy Team released Hy3, a 295-billion-parameter Mixture-of-Experts (MoE) language model with 21B active parameters and a 3.8B MTP layer. The model outperforms similar-sized models and rivals open-source models with 2-5x parameters. It is available on Hugging Face in full (598GB) and FP8 quantized (300GB) versions.
Tencent's Hy Team released Hy3, a 295-billion-parameter Mixture-of-Experts (MoE) language model with 21B active parameters and a 3.8B MTP layer. The model outperforms similar-sized models and rivals open-source models with 2-5x parameters. It is available on Hugging Face in full (598GB) and FP8 quantized (300GB) versions.
0 engagement1 sourcerssMon, Jul 6, 2026, 11:57 PM
Releases·Model Releasefeatured
DeepSeek V4.1 Flash is getting surprisingly close to GPT-5.6 Sol territory, while being absurdly cheap
DeepSeek released V4.1-Flash, an open-weight (MIT) MoE model built on a new causal encoder-decoder architecture with asymmetric active parameters — 8B for input/prefill and 16B for output/decode. The release adds vision input, 1M-token context, and aggressive KV-cache compression, drawing independent praise as the new top open-weight model on cost-adjusted intelligence. It succeeds V4 Pro, which DeepSeek is quietly retiring, and several commentators argue the '0.1 version' label understates a fundamental architectural overhaul.
DeepSeek released V4.1-Flash, an open-weight (MIT) MoE model built on a new causal encoder-decoder architecture with asymmetric active parameters — 8B for input/prefill and 16B for output/decode. The release adds vision input, 1M-token context, and aggressive KV-cache compression, drawing independent praise as the new top open-weight model on cost-adjusted intelligence. It succeeds V4 Pro, which DeepSeek is quietly retiring, and several commentators argue the '0.1 version' label understates a fundamental architectural overhaul.
Updated Sat, Sep 12, 2026, 05:56 AM — Ollama rolled out V4.1-Flash to Max and Team accounts, later expanding to Pro subscribers; Baseten offered day-0 hosting
2104.8k engagement3 sourcesreddit, x, rssThu, Sep 10, 2026, 07:56 AM
Releases·Model Releasefeatured
Dots Studio releases dots3-note preview, first open-weight dots3 model
Dots Studio released dots3-note preview, the first open-weight model in the dots3 family. It is a Mixture-of-Experts model with 280B total parameters, 16B activated parameters, and 512K token context support, capable of processing text, images, video, and audio while producing text outputs.
Dots Studio released dots3-note preview, the first open-weight model in the dots3 family. It is a Mixture-of-Experts model with 280B total parameters, 16B activated parameters, and 512K token context support, capable of processing text, images, video, and audio while producing text outputs.
111 engagement1 sourceredditThu, Aug 13, 2026, 09:46 PM
Releases·Model Release
Motif Technologies releases Motif-3, a 314B MoE model with 256K context
Motif Technologies has released Motif-3, a 314-billion-parameter Mixture-of-Experts language model with a 256K context window. The model is built from the ground up, suggesting a new architecture rather than a fine-tune. This release marks a significant entry in the large MoE model space.
Motif Technologies has released Motif-3, a 314-billion-parameter Mixture-of-Experts language model with a 256K context window. The model is built from the ground up, suggesting a new architecture rather than a fine-tune. This release marks a significant entry in the large MoE model space.
0 engagement1 sourcerssWed, Aug 12, 2026, 04:51 AM