Skip to content

Record a cross-family discovery wave on local-model workloads beyond memory and RAG - #223

Merged
seathatflowsinourveins merged 1 commit into
mainfrom
catalog/local-model-workloads-20260924
Sep 25, 2026
Merged

seathatflowsinourveins merged 1 commit into
mainfrom
catalog/local-model-workloads-20260924

Conversation

@seathatflowsinourveins

Copy link
Copy Markdown
Collaborator

This records a cross-family discovery wave on one question: which local-model workloads, beyond memory and RAG, are worth running on a 64 GB M5 Pro for the US-equities north star and native agent engineering. It is discovery evidence only. Nothing named here was installed, downloaded or executed, and inclusion selects nothing.

Method

  • One frozen packet went to two blind lanes. Neither lane saw the other's return or the catalogs.

    • The Claude lane ran on Opus 5.5 with web research.
    • The Codex lane ran on GPT-6 Astra at high effort with live web search, with --ignore-user-config and hooks disabled.
  • The lanes disagreed on one item: tabular foundation models for predicting +200% movers. A blind judge (GPT-6 Sol, high effort, live web search) reviewed the two returns three times, with lane identities scrubbed:

    • original order: skip listed second;
    • letters swapped: skip listed second;
    • listing reversed: skip listed first.

    All three judgments chose skip, so listing position is counterbalanced for this question.

  • The evidence directory holds the packet, the sealed lane returns with their original sha256, the adjudication inputs and key, the judgment record, provenance, native usage (null where unknown) and SHA256SUMS.

Outcome

catalogs/us-equities/local-model-workloads-20260924.json holds 9 repository decisions (registered through catalog_decisions.py) and 18 non-repository decisions (Hugging Face models pinned by revision).

Decision Items
Converged trial (both lanes) Catalyst tagging from 8-Ks: Qwen3.8-27B, with GLiNER2 as a CPU student. Earnings-call ASR: Cohere Transcribe 03-2026, Parakeet-TDT-0.6B-v3 on FluidAudio. Image-only exhibits: TeleOCR, PaddleOCR-VL-1.6. Volatility and volume features: Chronos-2, TTM r2.1.
Adjudicated skip TabICLv2 and TabPFN-3.5 for temporal equity prediction. Decisive evidence: BeyondArena (arXiv 2606.30410), and the TabPFN-3.5 report, which says tuned MLPs still lead its temporal and large subsets.
Single-lane lead Point-in-time dated checkpoints for backtest text features (PIT-4B-FT, ChronoGPT/ChronoBERT; Claude lane). Tool-output injection screening (PIGuard, Prompt Guard 2; Claude lane). Failure-log triage and editor next-edit (Codex lane).
Skip, not local The primary agent loop, return forecasting with time-series foundation models, text-to-SQL, filing Q&A and LLM judging.

Each item records its acceptance gate: a frozen dataset, a baseline and a metric. A trial becomes adoption only through an executed comparison.

Registration and counts

  • Identities: 850 → 857. New: GLiNER2, FluidAudio, mlx-audio, granite-tsfm, PIGuard, tabicl, TabPFN.
  • README.md, catalogs/us-equities/README.md, saturation-audit.json and manifests/evidence.json are updated (files rehashed, convergence record appended).

Limits

  • Single judge, from the same model family as the Codex lane.
  • Discovery depth only: no pinned-source review and no execution.
  • Pins were taken after the lanes ran.
  • The Claude lane's blindness is enforced by its prompt, not by a filesystem boundary.

Verification

  • validate.py, validate_catalogs.py, landscape.py, catalog_decisions.py --check, evidence_manifest.py --check, validate_convergence.py --all-recorded (21 records), saturation_ledger.py --check, build_verdicts.py --check, build_ecosystem.py --check and git diff --check: all exit 0.
  • The targeted test modules (204 tests) pass, including the blind-export isolation test.
  • Full python3 -m unittest: see the CI result.

🤖 Generated with Claude Code

…memory and RAG

Two blind lanes (Claude Opus 5.5 and Codex GPT-6 Astra) answered one frozen packet on which
local-model workloads earn a place on a 64 GB M5 Pro for the US-equities north star and native
agent engineering. One disagreement (tabular foundation models for +200% mover prediction) went
to a blind GPT-6 Sol judge three times, with the letters swapped and the listing order
reversed; all three judgments chose skip.

The supplement registers 9 GitHub repositories (identities 850 -> 857) and records 18 Hugging
Face-only models pinned by revision. Converged trials: catalyst tagging (Qwen3.8-27B with a
GLiNER2 student), earnings-call ASR (Cohere Transcribe, Parakeet with FluidAudio), image-only
exhibits (TeleOCR, PaddleOCR-VL-1.6), and volatility/volume features (Chronos-2, TTM r2.1). Each
records its acceptance gate. Discovery only: nothing was installed, downloaded or executed.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
@chatgpt-codex-connector

Copy link
Copy Markdown

You have reached your Codex usage limits for code reviews. You can see your limits in the Codex usage dashboard.
To continue using code reviews, add credits to your account and enable them for code reviews in your settings.

@seathatflowsinourveins
seathatflowsinourveins merged commit a73e077 into main Sep 25, 2026
22 checks passed
@seathatflowsinourveins
seathatflowsinourveins deleted the catalog/local-model-workloads-20260924 branch September 25, 2026 01:26
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

1 participant