Halogen

Headlines · 2

1. 6d
   Swift 1.5 benchmark shows coding-agent token savings on Strix Halo

   A r/LocalLLaMA user compared UkisAI’s Swift 1.5 fine-tune of Qwen3.8-Flash-Next with Unsloth’s quantization across Halogen, gufo and llama.cpp on an Asus ROG Flow Z13 with 128 GB of memory and a 70 W power limit. Swift produced 56,000–63,000 output tokens across 11 Pi coding-agent tasks, versus 75,000–99,000 for Qwen3.8-Flash-Next, and the gufo Swift setup completed them in 24 minutes compared with 33 minutes for gufo with Unsloth’s UD-Q4_K_XL. The results were mixed on math and LiveCodeBench, and the author cautioned that they came from a single run, so differences of one or two solved problems could reflect chance.

   r/LocalLLaMA · 🔥 0
2. Oct 20
   Qwen3.8-Flash-Next runs close behind Claude Opus 5.5 in a six-way coding benchmark

   A Reddit user (deepu105, r/LocalLLaMA) ran a controlled comparison on one real Rust feature from the LlamaStash roadmap, testing six model-harness-effort combinations twice for 12 pull requests; Flash-Next ran locally on a Strix Halo laptop (Flow Z13) via Halogen at roughly Q4 quantization, while Opus 5.5 ran through Claude Code. Claude Code with Opus 5.5 at xhigh effort scored 6.94 of 8 (87%) in 43.5 minutes at $17.78 of API cost, while Claude Code with Flash-Next at medium scored 5.5 of 8 (69%) in 45.3 minutes; the author reports Opus averaged 82% on code quality versus 68% for Claude Code + Flash-Next and 66% for Pi + Flash-Next, with the gap concentrated in edge cases, tests and documentation. All 12 runs finished and all 12 PRs passed the end-to-end test, and the author notes the models are not in the same league since Flash-Next ran quantized on a 70W-capped laptop.

   r/LocalLLaMA · 🔥 0

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