Unsloth

Zhipu AI has released GLM-5.3-Flash, the first natively multimodal model in its GLM-5 series, built on a 320B-parameter mixture-of-experts architecture with only 18B active parameters. The company claims it outperforms GLM-5.2 while approaching Claude Opus 4.8 on coding and agentic benchmarks at a fraction of the cost. Unsloth has published quantized GGUF versions for local inference.

Qwen3.8-Flash-Next is an experimental preview of the architecture Alibaba's Qwen team plans to use for Qwen4, combining hybrid attention, gated residuals, and n-gram embeddings in a 125B-parameter model with only 6B activated per token. Unsloth has released Dynamic 3.0 GGUF quantizations for local inference.

Unsloth has published GGUF quantizations of Muse Glimmer-30B, a dense 29.6B-parameter causal transformer with a dedicated perception encoder, attributed to Meta Superintelligence Lab in the model card. The model targets autonomous agentic tasks on consumer hardware with a 131,072-token context window and 4-bit quantization under 20GB.

DeepSeek has shipped the full release of DeepSeek-V4-Flash-0731, a 284B-parameter model that according to DeepSeek outperforms its own larger V4-Pro (Preview) on agentic and coding benchmarks. Unsloth has published quantized GGUF versions, with lossless 8-bit weights requiring 162GB of storage.

Unsloth has released GGUF quantizations of Kimi K3, a 2.8-trillion-parameter open-weight Mixture-of-Experts model from Moonshot AI with a 1-million-token context window and native vision support. The largest lossless quantization (Q8) weighs in at 1.56TB.

Moonshot AI has released Kimi K3, a 2.8-trillion-parameter open-weight mixture-of-experts model with a 1-million-token context window and native multimodal support. Unsloth has published Dynamic 2.0 quantized versions on Hugging Face, claiming improved accuracy over other quantization methods.

Unsloth has released optimized GGUF quantizations of DeepSeek-V4-Flash, a 284B parameter Mixture-of-Experts model that activates 13B parameters and supports 1 million token context windows. The Q8 quantization (UD-Q8_K_XL) runs at 162GB with claimed lossless precision, only 7GB larger than the Q4 variant.

IBM has released the Granite 4.1 family of language models under Apache 2.0 license. The models come in 3B, 8B, and 30B parameter sizes. Unsloth has released 21 GGUF quantized variants of the 3B model ranging from 1.2GB to 6.34GB.