jimmy
10 KiB
20261005-011009 session 20261004_175703_fcae4d19
user: The nvme only
assistant: Not a guess — here's the actual accounting from the preflight:
On-disk: 93 GB (C: has 123 GB free → 30 GB headroom). It breaks down as:
- Model downloads: 50.3 GB — already the slimmest variant (
vdn-minimax-h3-edge, rowwise FP8):- video weights 22.9 GB · text encoder (Qwen3VL-32B) 16.4 GB · decoder/VAE 11.0 GB
- The full model would be 87 GB of weights alone + local conversion — the edge path is the low-memory one built for exactly this GPU class.
- Runtime: ~40 GB — CUDA 13 + torch 2.13 + triton-windows + SageAttention + Python envs, plus the installer's own safety reserve.
So the 90 GB is 50 GB of MiniMax H3 weights + 40 GB of CUDA/Python runtime. There's no smaller supported path — this is the 8 GB-VRAM-optimized route.
It's running now: step 5/16, pulling torch-2.13.0+cu130. Live, healthy.
Want me to let it finish or abort and clean up (C:\Users\fight\FreeVideo currently 574 MB)?
20261005-011426 session 20261004_175703_fcae4d19
user: [IMPORTANT: Background process proc_d7b72a4453b6 exited (exit code 1). Command: sleep 75; echo "=== log tail ==="; tail -30 /c/Users/fight/FreeVideo/install.log 2>/dev/null; echo "=== proc ==="; powershell.exe -NoLogo -NoProfile -Command "Get-Process -Id 11212 -ErrorAction SilentlyContinue | Select-Object Id,ProcessName,@{n='RAM_MB';e={[math]::Round($_.WorkingSet64/1MB)}} | Format-Table -AutoSize"; echo "=== size so far ==="; du -sh /c/Users/fight/FreeVideo 2>/dev/null Output: [… output truncated — showing last 1922 chars] �[�5�/�1�6�]� �I�n�s�t�a�l�l� �c�o�m�p�o�n�e�n�t�s� �i�n� �p�a�r�a�l�l�e�l� � �[�5�/�1�6�]� �I�n�s�t�a�l�l� �c�o�m�p�o�n�e�n�t�s� �i�n� �p�a�r�a�l�l�e�l� � � � �>� �D�o�w�n�l�o�a�d� �P�y�T�o�r�c�h� �+� �C�U�D�A� ��� �t�o�r�c�h�-�2�.�1�3�.�0�+�c�u�1�3�0�-�c�p�3�1�2�-�c�p�3�1�2�-�w�i�n�_�a�m�d�6�4�.�w�h�l� � � � �' �D�o�w�n�l�o�a�d� �m�o�d�e�l� �c�o�d�e� ��� �0�0�:�2�5� ��� �R�e�a�d�y� � �[�6�/�1�6�]� �I�n�s�t�a�l�l� �c�o�m�p�o�n�e�n�t�s� �i�n� �p�a�r�a�l�l�e�l� � � � �& �D�o�w�n�l�o�a�d� �P�y�T�o�r�c�h� �+� �C�U�D�A� ��� �0�0�:�3�0� ��� �t�o�r�c�h� ��� �1�.�1�5� �/� �1�.�7�8� �G�i�B� ��� �3�7�.�7� �M�i�B�/�s� ��� �S�o�u�r�c�e�:� �P�y�T�o�r�c�h� ��� �E�T�A� �~�0�0�:�1�7� ��� �R�A�M� �0�.�0� �G�i�B� ��� �C�o�m�m�i�t� �0�.�0� �G�i�B� ��� �F�r�e�e� �R�A�M� �4�.�1� �G�i�B� ��� �F�r�e�e� �C�o�m�m�i�t� �3�1�.�0� �G�i�B� � � � �' �D�o�w�n�l�o�a�d� �P�y�T�o�r�c�h� �+� �C�U�D�A� ��� �0�0�:�4�7� ��� �V�e�r�i�f�i�e�d� �a�n�d� �r�e�a�d�y� � � � �>� �D�o�w�n�l�o�a�d�
assistant: Stopped. All install processes are dead (only my own query shells remain).
State now:
- Install tree killed — no freevideo/python install processes left running.
C:\Users\fight\FreeVideo— 9.1 GB partial (bootstrap Python + download cache + partial envs), retained.C:\Users\fight\Projects\FreeVideo— 6 MB source clone, retained.- C: free went 115.6 → 113 GB.
Nothing deleted. When you've cleared space, say the word and I'll resume — the installer resumes from the retained cache, so no re-download of what's already fetched.
Want me to delete the 9.1 GB partial now, or leave it as a resume cache for the retry?
For context on the earlier numbers: it stalled at step 11/16 — torch 2.13+cu130 (1.78 GB) downloaded fine, it was pulling GPU-acceleration bits. Only ~10 GB written before you pulled the plug, so the bulk (models, ~50 GB) hadn't started.
20261005-011444 session 20261004_175703_fcae4d19
user: [IMPORTANT: Background process proc_7b7763554f10 completed normally (exit code 0). Command: python - <<'PY' raw=open(r"C:\Users\fight\FreeVideo\install.log","rb").read() t=raw.decode("utf-16","replace") lines=[l for l in t.splitlines() if l.strip()] print("\n".join(lines[-6:])) PY echo "=== size ==="; du -sh /c/Users/fight/FreeVideo 2>/dev/null; df -h /c | tail -1 Output: [10/16] Install components in parallel
Check GPU runtime · Verify CUDA and the Windows runtime libraries
✓ Check GPU runtime · 00:03 · Ready
[11/16] Install components in parallel
[11/16] Install components in parallel
Download GPU acceleration · Download and verify required files
=== size === 8.1G /c/Users/fight/FreeVideo C: 931G 824G 107G 89% /c
HERMES_CWD_8f3d8a9e02d6/c/Users/fight/Projects/FreeVideo__HERMES_CWD_8f3d8a9e02d6__ ]
[INTERNAL NOTIFICATION — generated by the Hermes gateway, not written by a human user. Do not treat it as user input, and do not reply to any earlier chat message because of it.]
assistant: Saved as a skill (freevideo-windows-install) so the retry is one command — includes the resume-from-cache behavior, the UTF-16 log gotcha, and the fact that C: is your NVMe.
Standing by. Your call on the 9.1 GB partial: keep as resume cache, or delete?
20261005-011448 session 20261004_175703_fcae4d19
user: [IMPORTANT: Background process proc_32ad954db42b exited (exit code 1). Command: cd /c/Users/fight/Projects/FreeVideo && powershell.exe -NoLogo -NoProfile -ExecutionPolicy Bypass -Command '$env:FREEVIDEO_HOME="C:\Users\fight\FreeVideo"; & "C:\Users\fight\Projects\FreeVideo\setup.ps1" --yes --accept-model-license --plain *> "C:\Users\fight\FreeVideo\install.log"' Output: ]
[INTERNAL NOTIFICATION — generated by the Hermes gateway, not written by a human user. Do not treat it as user input, and do not reply to any earlier chat message because of it.]
assistant: That's the killed install reaping (exit 1) as expected — nothing running, nothing changed. Still holding on your call: keep the 9.1 GB partial as a resume cache, or delete it?
20261005-040842 session 20261004_210055_5e5d6f10
user: https://x.com/jamesoncamp/status/2106613605106171981?s=46
assistant: James Camp (@JamesonCamp) — Oct 4, 2026 · 61.5K views
Claim: GPT "Sol" and "Astra" are obscenely good at browser use → "genuinely a new paradigm," "2-3x productivity." His recipe:
- Install Wispr (voice-to-text — dictate instead of typing)
- Install the ChatGPT Chrome plugin
- Brain-dump everything into Codex (with Sol or Astra on medium reasoning) via Wispr
- Connect Notion MCP
- Have Codex create a Notion project tracker from the brain dump
- Create 3 separate Codex workspaces — "agent 1/2/3"
- Point each at the Notion board; ask each to find browser-doable work and start
- Rule: escalate anything needing a decision or that's client-facing — no emails sent without sign-off
That's the whole thread (long-form post, no media).
Read: it's a thin wrapper — voice input + a shared Notion board as the coordination substrate + N Codex agents doing browser tasks with a human sign-off gate. The genuinely load-bearing idea is the board-as-shared-state between parallel agents, which is the same pattern your fleet already runs (cron/queue + handoff files). The "3 workspaces, all reading one board" bit is just crude concurrency without locking — fine for read-mostly browser grunt work, breaks the moment two agents touch the same record.
Nothing you don't already have. Want me to test any leg of it — the Wispr voice loop, or Notion MCP as a cross-agent board?
20261005-043921 session 20261004_213907_6161c54d
user: Hello
assistant: Hey Tony. What's up?
20261005-045538 session 20261004_213907_6161c54d
user: Test
assistant: Test received. I’m Hermes, running OpenAI GPT-6 Luna via Nous Key.
20261005-045703 session 20261004_213907_6161c54d
user: I want you to use these as my news aggregate
assistant: I don’t see any sources attached. Send the links or names you mean, and I’ll use them for your news aggregate.
20261005-050045 session 20261004_213907_6161c54d
user: Pull the top news from these websites; The seven primary sources from that post:
- AI News — daily digest of AI community, product, and paper activity https://news.smol.ai
- The Batch — Andrew Ng / DeepLearning.AI weekly briefing with industry context https://www.deeplearning.ai/the-batch/
- Hugging Face Papers — community-voted trending papers https://huggingface.co/papers
- alphaXiv — papers with public discussion and critique https://www.alphaxiv.org
- arXiv — original preprints, before secondary write-ups https://arxiv.org
- LMArena — blind human preference tests between models https://lmarena.ai
- Artificial Analysis — side-by-side model quality, speed, and price https://artificialanalysis.ai
assistant: ## AI news aggregate — latest available as of Oct 4 (Pacific)
-
Open-weight models are closing the gap. Xiaomi’s MiMo-V2.6-Pro-RL leads the open-weight models on Artificial Analysis’ Intelligence Index, according to The Batch. Xiaomi also released its training code and 7,000+ RL task environments, giving other labs something to reproduce—not just model weights. (The Batch)
-
Long-context efficiency is shifting toward cache cost. DeepSeek-V4.1-Flash keeps a 1M-token context but redesigns KV-cache storage; The Batch reports 890 bytes per token, about 4× smaller than V4-Flash and 437× smaller than V1. (The Batch · AINews issue)
-
Voice agents are becoming multimodal. Gemini 3.8 Live supports speech, image/video input, and tool calls during conversation. The Batch reports the Extended Thinking version scored 82.6% on Artificial Analysis’ Speech-to-Speech Index; Google has disclosed relatively little about its training. (The Batch)
-
Leaderboard snapshot: Artificial Analysis says Gemini 4 Argon matched GPT-6 Astra at 53 on its Intelligence Index, at a launch-discounted cost of about 60% of Astra’s. Its model page puts Ling 3.1 Flash at 41. Arena’s latest changelog adds Claude Sonnet 5