Video summary

Grok 4.6 is Fable now

Main summary

Key takeaways

Technology

Tech/Model update: Grok 4.6 vs top frontier models

  • Grok 4.6 release is reported as achieving benchmark parity / “neck-to-neck” with:
    • Fable 5 Max (described as an OpenAI frontier competitor in the transcript)
    • Anthropic’s best model (referred to as “Opus” / “Fable” family in the subtitles)

Key training delta vs Grok 4.5

  • Much longer supplemental training run for Grok 4.6
  • Both are described as variants of a 1.5T parameter base model (“V9 model” / “base”)
  • Grok 4.6 uses more data—especially from Cursor—including curated model-generated data for:
    • reasoning
    • advanced technical concepts
    • high-quality engineering data
  • Mentions:
    • an improved optimizer
    • an updated training recipe
  • Claim: this strengthens later supervised fine-tuning and reinforcement learning stages

Benchmark skepticism acknowledged

The speaker notes that benchmarks can sometimes be “gamed,” but claims early hands-on results look strong rather than failing basic tests.


Hands-on demo claims (Portal 2 + interactive 3D)

  • The speaker runs a Grok 4.6 build (with high settings; they later mention extra high exists).
  • First test: prompt a “clone” of Portal 2, resulting in:
    • generation of game mechanics (blue/orange portals)
    • creation of 3D objects, a room, lighting/reflections, and puzzle logic “in one shot”
    • portal rendering/behavior like momentum conservation
  • Multimodal-ish extras via external tooling:
    • the speaker mentions adding sound effects and voiceovers using ElevenLabs

“Chamber 07” segment

  • Includes:

    • reflections + lighting
    • both gates alive
    • ability to walk through portals while preserving momentum
  • Overall impression: Grok 4.6 feels like a high-end model (“a beast,” per the speaker).


Pricing + performance modes

Quoted pricing (subtitles)

  • $2 per 1M input tokens
  • $6 per 1M output tokens

“Fast” variant

  • Described as twice the price, but also twice the speed / usage
  • Roughly “evens out” for launch-week usage limits.

Launch-week availability detail

  • Using Cursor or Grok Build during launch week yields double usage for the new models.
  • Speaker advice: take advantage of this.

Tutorial-style automation concept: Cursor-driven “AI streamer” for games

The speaker describes an ongoing test to build a fully AI-automated run:

  • Game: Pokemon Red
  • System: a Pokemon Red emulator
  • Controls: the AI connects to a harness to control the game
  • Output: generates text-to-speech narration
  • Avatars: a video avatar idea is mentioned to explain what’s happening
  • Interaction: AI can talk to chat
  • Safety: adds censorship / anti-jailbreak so it won’t get misused

Status

  • The prototype can already:
    • load the game
    • pass initial screens
    • create components like fake chat and TTS voiceover
  • Note: the system may still get stuck on logic later in the run.

Leaderboard-style evaluation: GPT-4o-style “GPTVal”

  • Mentions GPTVal as a benchmark:
    • evaluates real-world job tasks/projects across industries, including:
      • engineering
      • AutoCAD
      • hospitality/travel agent work
      • finance
      • video editing
  • Claim: Grok 4.6 beats Fable 5 and other competitors.
  • Why it matters: positioned as more predictive of agentic work quality, aligning with Grok’s always-on agent product.

Grokbot: always-on agent (digital labor), teachable workflows

What Grokbot is

  • Described as:
    • always on / always online / always available
    • an agent team rather than a traditional chatbot
  • Available on:
    • desktop apps: Linux / Mac / Windows
    • Android coming soon

Architecture detail

  • Each agent runs with its own cloud virtual machine
  • Purpose: work 24/7 even if the user’s computer is off.

Role workflow (“chief of staff”)

  • Speaker suggests creating a “chief of staff” role:
    • it delegates tasks to sub-agents automatically
    • user speaks to one point of contact while it coordinates others

“Teach a task” feature

  • Grokbot includes a button to teach tasks by recording the user’s actions/steps.
  • Motivation: avoid dangerous behavior like an agent accidentally sending messages in chat apps (speaker cites a prior incident with another model).
  • “Teach a task” lets users define safe, repeatable skills for agent execution.

Example agents built

  • X news / real-time X (Twitter) monitor
    • searches X for relevant posts
    • reports whether “Elon said something,” etc.
  • Speaker attempts to determine whether Grok 4.6 is live on Grokbot:
    • no confirmation of the exact model, but “likely coming very soon”
  • Agent can create routines like:
    • checking 3 times/day for 10 days, then notifying the user

UX/product polish highlighted vs competitors

  • Speaker praises Grokbot UI patterns:
    • more frequent choice boxes / quick options to reduce cognitive load
    • at-a-glance answers enabling faster decisions (less reading/typing)
  • Comparison note:
    • contrasts with “Fable 5,” described as having an odd speaking style or lots of rambling/memes
    • claims Grok feels faster and more direct in active use

Future roadmap speculation (Grok 4.7, Grok 5)

  • Expected cadence/targets mentioned:
    • Grok 4.7 expected in 3–4 weeks
    • potentially a larger 2.1T parameter model (explicitly framed as rumor/speculation)
    • Grok 5 targeted before end of year
  • Reason for rapid cadence:
    • speaker claims XAI reorganized engineering to ship major updates every 2–3 weeks
  • Training data rumor:
    • mentions large amounts of SpaceX company data used for supplemental training for the next release (attributed to a future model described in the transcript)

Pricing/competition positioning (speaker’s take)

  • Speaker argues Grok 4.6 pricing is lower than comparable frontier models
  • Claims XAI + Cursor partnership may help it win
  • Mentions “Google lagging slightly behind” as general competitive commentary

Main speakers / sources (as identified in subtitles)

  • Speaker: Wes Roth (ends with “My name is Wes Roth”)
  • Referenced organizations/products:
    • XAI
    • Anthropic
    • “Fable” (as named in subtitles)
    • OpenAI (implied)
    • Cursor
    • Grokbot
    • Grok Build
    • Grok 4.6 / 4.5 / 4.7 / 5
    • ElevenLabs
    • WhatsApp / Slack
    • X (Twitter)

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