Qwen3.8-27B Articles
Browse 9 articles about Qwen3.8-27B.
Thinking Cap vs Swift 1.5 vs Qwen Pi: Best Qwen3.8-27B Fine-Tune?
Three teams fine-tuned Qwen3.8-27B to think less without losing accuracy. Here's how Thinking Cap, Swift 1.5, and Qwen Pi actually compare.
OrcaSAQ2 27B Benchmarks: How a 3-Bit Model Rivals Claude on SWE-bench
OrcaSAQ2 27B hits 70% on SWE-bench Verified and 58.4% on Terminal-Bench 2.1 from a 12.3 GB checkpoint. Here's what the numbers actually mean.
Run Bonsai 2 27B Locally on a Mac: Ternary Quantization Explained
Bonsai 2 27B compresses a 27B reasoning model to 8.6GB with ternary weights, hitting ~47 tok/s on an M5 Max MacBook via MLX.
Hemmingway-1: The 27B Open Model Trained to Write Like a Person
Hemmingway-1 is a 27B Apache-2.0 model tuned for everyday writing that claims to beat GPT-6 Astra and Kimi K3 on human-likeness tests.
2-Bit vs FP8 Quantization: What the Escha-W2 Benchmarks Show
Escha-W2 compresses a 27B model to 2-bit and matches FP8 on GPQA, LiveCodeBench, and commonsense tests. Here's what that means for local inference.
What Is DFlash 2? Speculative Decoding Explained for Qwen3.8-27B
DFlash 2 is a block-diffusion draft model that speeds up Qwen3.8-27B inference up to 3.4x. Here's how it works and what it beats.
Qwen3.8-27B OBLITERATED: How This Uncensored Model Actually Works
A breakdown of Qwen3.8-27B-OBLITERATED V2, an abliterated model with a 0% refusal rate that matches or beats stock MMLU scores.
DFlash 2: Run Qwen3.8-27B at 2x Speed with Speculative Decoding
DFlash 2 speeds up Qwen3.8-27B inference roughly 2x on a single A100 using speculative decoding in SGLang, with no output quality loss.
Qwen3.8-27B AEON Uncensored: How This Abliteration Actually Works
A community abliteration of Qwen3.8-27B explains its KL-drift methodology, judge-based refusal testing, and how to run the model via vLLM.