Fable Refusals, OMP Harness, Video Routing — AI Daily Jul 14

385 messages · 63 active members

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63
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@jcartu, @samb69, @fuckyesiwannatalkbusiness
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Overview

Model wars dominated the day, with Fable 5's aggressive safeguards pushing builders toward Sol and GPT-5.6. @jcartu vented about Fable burning tokens then refusing basic sysadmin tasks (media player setup, file cleanup), while Sol quietly complied. A shared kilo.ai post reinforced the pattern: Sol writes better plans, and the execution model matters less than the planner. Several members are rethinking their subscription stacks — cancelling Anthropic seats, downgrading GPT plans, and upgrading Grok to the $300 tier (available for $99/3mo). OMP (omp.sh) emerged as the harness of the day, with @jcartu and @samb69 pitching it as a unified replacement for Claude Code and Codex — one interface across all OAuth and API accounts, auto-switching models per role, and even routing to local GPUs. @thewildzeno confirmed it feels fast but flagged terminal rendering glitches outside Arch. Meanwhile @iamgalba is running 4-5 overnight Codex sessions via tmux with subagent teams, and shared a video pipeline where agent-based model routing cut a 70-segment midform down to ~$30, echoed by @samb69 dropping Seedance video costs from $8-12 to ~$2. On the infra side, @jcartu shared a hybrid MXFP8/NVFP4/NF3 quantization of GLM 5.2 that stays within 1% KLD of BF16 — beating z.ai's cloud FP8 — though he noted GLM is mainly worth self-hosting for compliance-sensitive workflows. A Bloomberg leak about Apple's 1.5TB M7 Ultra also kicked off a long NVIDIA-vs-Apple local-inference debate, and @GuruTime resolved a Meta Ads dev-mode error (flip to Live, no App Review needed).

Topics

Fable 5's broad safeguards are flagging routine coding and sysadmin tasks, burning tokens before refusing or downgrading to Opus 4.8. @jcartu reported Sol completed a media-player install that Fable rejected, and a shared kilo.ai analysis showed Sol produces better execution plans regardless of which model runs them.

@jcartu and @samb69 championed omp.sh as a single harness that wraps all OAuth/API accounts and local GPUs, auto-switching models by role. @thewildzeno confirmed the speed but noted terminal rendering glitches outside Arch Linux. Users are pairing it with GPT-5.6 + Grok 4.5 for fast default execution.

@iamgalba detailed an agent-based routing setup across Seedance, Veo, WAN 2.7, and Grok Imagine 1.5 that produced 70-segment midform videos for ~$30. @samb69 reported similar wins, dropping Seedance video costs from $8-12 to ~$2 per video, with @arielletolome praising WAN 2.7 for B-roll generation.

@jcartu shared a MXFP8/NVFP4/NF3 hybrid quantization of GLM 5.2 that stays within 1% KLD of BF16 — better than z.ai's FP8 cloud serving. He clarified GLM is mainly useful for compliance-sensitive tasks, as Fable and GPT-5.6 outperform it when they comply.

Grok 4.5's ~1000 tps speed is convincing members to restructure subs — cancelling Anthropic seats, downgrading GPT to $100, and upgrading Grok to the $300 tier (currently $99 for 3 months). @samb69 uses Sol as advisor and Grok as the fast executor for hours-long chained workflows.

Key Takeaways

  • Fable 5's safeguards are flagging routine dev work — keep Sol or GPT-5.6 as a fallback in your harness to avoid wasted tokens
  • OMP (omp.sh) unifies Claude Code, Codex, and local GPU inference under one harness with per-role model auto-switching
  • Agent-based routing across video models can cut UGC production costs 4-6x; Grok Imagine 1.5 leads on price-to-quality
  • Hybrid NVFP4/NF3 quantization of GLM 5.2 achieves <1% KLD vs BF16, beating cloud FP8 — but only worth self-hosting for compliance workflows
  • Grok 4.5 at ~1000 tps is fast enough to be the daily executor under a Sol/Fable planner; $300 tier is $99 for 3 months right now

Hot Threads

@jcartustarted

Fable refusing sysadmin tasks while Sol complies

18 replies8 participants
@iamgalbastarted

Agent-routed video pipeline cutting UGC costs in half

14 replies6 participants
@jcartustarted

Running GLM 5.2 locally with near-lossless hybrid quantization

16 replies5 participants

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