AINewsnow

Solving a complex multi-task with 262k vs 128 context dropped performance from 91% to 57%... Then I made two changes. Solves with 128k went up to 94%.

I've been benchmarking local models as coding agents in opencode on real bugs in a real codebase, graded by hidden tests. The hardest tasks bundle 6–12 independent bugs into one request. At a 128k window, Qwen3.8-Flash-Next (IQ3_XXS, 2× 7900 XTX) kept "finishing" early with half the bugs untouched.…

Read the full story at r/LocalLLM ↗

Timeline · 1 report

  1. 2026-11-01 01:42 · r/LocalLLM
    Solving a complex multi-task with 262k vs 128 context dropped performance from 91% to 57%... Then I made two changes. Solves with 128k went up to 94%.

More stories

  1. Mistral releases weights for trillion-parameter Le Chonk model with 1M-token context — Wired AI
  2. Foxconn hints at new OpenAI tie-up for AI hardware, says no AI bubble — Economic Times Tech
  3. Big Tech sheds nearly $900bn as AI spending fears trigger market rout — Financial Times AI
  4. DeepSeek Releases Enhanced Coding Agent to Rival Anthropic's Claude Code — Bloomberg AI
  5. OpenAI cuts fundraising target to $20 billion amid AI market selloff — Financial Times AI
  6. Renesas projects 26.4% revenue growth in 2026 on AI data center demand; Nebius leases 50 MW capacity — DigiTimes Asia
  7. Google, Microsoft, OpenAI and Anthropic to honor shared robots.txt AI training opt-out — OpenAI News
  8. Apple CEO John Ternus says company won't ship AI for AI's sake — Techmeme

Get the daily brief of stories like this at 6:30 every morning →