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Models2026-09-15 · source-backed
IFM's lineup showed up on the Artificial Analysis Intelligence Index with the 7B slotting between two much larger Qwen models (r/LocalLLaMA). Two corrections from the thread and the model card: the HF config reports about 8.999B parameters in BF16 for a dense model, and the README states 18.0 GiB of KV cache at 128K tokens, which the top comment argues disqualifies the "GPU poor" framing. Apache 2.0, created September 1, 7,447 downloads.
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Somebody diffed the configs. Zero architectural changes. Same 64 layers, same 5,120 hidden dimension, same hybrid Gated DeltaNet → FFN / Gated Attention → FFN block structure as Qwen3.6-27B. The r/LocalLLaMA post showing this hit 945 upvotes and 157 comments, and Hugging Face...
Google DeepMind released Gemma 4 on April 2 with four model sizes (E2B, E4B, 26B MoE, 31B Dense) under Apache 2.0. Multimodal (text, vision, audio). 256K context. Native thinking and tool-calling optimized for agentic workflows. Day-zero ecosystem support across vLLM, llama.cp...
Ollama cut v0.34.0-rc1 on September 5 at 23:49 UTC, and the headline item changes the shape of the local-versus-hosted decision rather than the performance of either side: Ollama-hosted open models can be selected directly inside ChatGPT Desktop, with setup driven from the Oll...
The models are good. The license is the real story. Google released Gemma 4 on April 2 with four variants: E2B, E4B, 26B MoE, and 31B Dense. All built on the Gemini 3 architecture. The 31B Dense variant claimed #3 on Arena AI's text leaderboard, beating models 20x its size. Th...
Alibaba released Qwen3.6-27B on April 22. Dense architecture. Open weights. 77.2% on SWE-bench Verified, within 3.7 points of Claude Opus 4.6. On SkillsBench, it scores 48.2% versus its own 397B MoE predecessor's 30.0%. That's a 77% improvement with 14.8x fewer parameters. Let...
Moonshot AI dropped Kimi K2.6 today and the numbers are hard to ignore. One trillion parameters total, 32 billion active per token across 384 experts, 256K context window, and native multimodal input. It scores 58.6 on SWE-Bench Pro versus GPT-5.4's 57.7 and Claude Opus 4.6's...
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