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u/trainermade

r/Strong_8K r/hermesagent r/MiniMax_AI
▲ 11 r/MiniMax_AI

Model Stacking GLM 5.2 and Minimax 3

Dan does a great job of explaining how close, or far, according to some, the open source vs. SOTA model race is. Really enjoyed this video https://youtu.be/cFYdiynrxpQ?si=0vamlAqO3rx0FKV2

For those who frequently complain here, it's important to note that open-source models aren't designed to compete at the highest levels. They are great bargain-bin daily drivers and more than adequate for 90% of the work we expect to get done.

u/trainermade — 6 days ago
▲ 3 r/MiniMax_AI

Since M3 is multimodal, to create images do we use the M3 model?

Looking at the documentation here https://platform.minimax.io/docs/guides/image-generation the payload still has image-01 as the model.

payload = {
"model": "image-01",
"prompt": "men Dressing in white t shirt, full-body stand front view image :25, outdoor, Venice beach sign, full-body image, Los Angeles, Fashion photography of 90s, documentary, Film grain, photorealistic",
"aspect_ratio": "16:9",
"response_format": "base64",
}

so now instead of image-01, should we use MiniMax-M3 as the model name there?

u/trainermade — 1 month ago
▲ 3 r/MiniMax_AI

MiniMax loses bid to dismiss Disney copyright lawsuit over AI system

A US federal court has rejected Chinese AI company MiniMax’s attempt to toss out a copyright infringement lawsuit brought by some of Hollywood’s biggest studios. The ruling keeps alive claims that MiniMax scraped protected content, including Marvel and Star Wars characters, to train its Hailuo AI image and video generation system.

China's MiniMax loses bid to end Disney copyright lawsuit over AI system | Reuters

reddit.com
u/trainermade — 1 month ago
▲ 5 r/MiniMax_AI

Context window issue through Anthropic endpoint - is the practical limit lower than 204.8k?

I’m using MiniMax-M2.7-highspeed through an Anthropic-compatible endpoint inside an agent framework called Hermes.

MiniMax appears to advertise a large context window, around 204,800 tokens, but I’m seeing API failures well below that.

The error looks like this:

⚠️  API call failed (attempt 1/3): BadRequestError [HTTP 400]
   🔌 Provider: minimax  Model: MiniMax-M2.7-highspeed
   🌐 Endpoint: https://api.minimax.io/anthropic
   📝 Error: HTTP 400: invalid params, context window exceeds limit (2013)
   📋 Details: {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'invalid params, context window exceeds limit (2013)'}, 'request_id': '065b1bb0eab63a4b21e50cb78514'}
   ⏱️  Elapsed: 2.61s  Context: 106 msgs, ~134,146 tokens
Provider reported overflow amount only; keeping context_length at 204,800 tokens and compressing.
⚠️  Context length exceeded at minimum tier — attempting compression...
🗜️ Context too large (~134,146 tokens) — compressing (1/3)...
🗜️ Compacting context — summarizing earlier conversation so I can continue...

My questions:

  1. What does the number in this error mean?
reddit.com
u/trainermade — 2 months ago
▲ 1 r/hermesagent

Constant compaction - why?

Processing img z1yb3e61rx1h1...

Why does compaction happen at token 106k when my token max is 204k? Started seeing this alot recently.

reddit.com
u/trainermade — 2 months ago
▲ 1 r/hermesagent

I am looking to move my Hermes VPS implementation from a reactive chat tool to a persistent agent similar to "Felix" from the Nat Eliason interview: https://www.youtube.com/watch?v=nSBKCZQkmYw
I have a few questions on the mechanics of proactivity:

  1. The Wake Up Trigger: How does the agent theoretically "wake itself up" to perform unprompted actions? For example, if a bug is reported or a new feature is requested via a ticket, do you use an MCP to trigger an interrupt, or a persistent heartbeat loop that polls for new tasks?

  2. Autonomous Coding: For a bot that builds its own features, how are you handling the handoff to worker sessions? I want the agent to identify a bug, spawn a persistent worker to fix it, and notify me only when the PR is ready. How do you prevent the OS from killing these long sessions?

  3. Memory Consolidation: For 24/7 operation, how do you handle nightly context cleaning? I want the agent to extract "nuggets" from the day into a knowledge graph without overwriting core system rules or hallucinating data.

If you have structured a "Heartbeat" skill or a specific config for proactive workflows, I would love to see how you are bridging that gap.

u/trainermade — 2 months ago