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Live Vibe Check: OpenAI's Super-fast Spark Model Running at 1,000 TOKENS / S

| 14 products mentioned
Every Every host
Watch on YouTube coding models ai speed optimization prompt engineering ui/ux iteration knowledge work automation model selection strategy real-time ai interaction

The hosts conduct a live vibe check of OpenAI's Spark model, a new ultra-fast coding model running at 1,000 tokens per second that fundamentally changes how developers interact with AI coding tools. Rather than simply being "smarter," Spark's extreme speed enables new use cases like real-time brainstorming, rapid prototyping, and interactive UI iteration—forcing a rethinking of best practices around agent orchestration, mega-prompts, and when speed matters more than raw intelligence. The episode explores how this speed threshold changes the ergonomics of AI-assisted development and what types of tasks this model excels at versus where smarter models like Opus or Codex 5.3 remain superior.

Key takeaways
  • Speed as a form of intelligence: Spark's 1,000 tokens/second throughput is so fast that OpenAI artificially slowed it down because users found the raw speed disconcerting, indicating we're entering a new paradigm where generation speed is as valuable as model intelligence.
  • Tool calls are now the bottleneck: With tokens generating near-instantaneously, orchestration overhead from sub-agents and tool calls becomes the slowest part of the pipeline, potentially making mega-prompts more efficient than agent swarms for certain tasks.
  • Spark excels at iterative, real-time tasks like brainstorming, vibe coding, rapid UI prototyping, and knowledge work queries where staying "in flow" matters more than perfection, but struggles with complex reasoning and deep debugging.
  • Voice-enabled coding is now feasible: Spark's speed makes interactive voice-based code generation viable with good interruption handling and turn-taking, representing the next frontier for coding models.
  • Context window management becomes critical: Spark uses context quickly and doesn't have the capacity for extremely large tasks, forcing developers to reconsider how they structure prompts and context.
  • Best practices change every 3-6 months as model constraints shift—developers at the edge must be willing to discard old approaches (agent swarms, complex orchestration) and return to simpler patterns when bottlenecks change.

Recommendations (7)

React
React uses

"I just use React here instead of HTML"

Live Vibe Check · ▶ 1:14:34

OpenAI Spark

"I use it for certain tasks where I need a ton of speed, but I don't care as much about the smartness"

Every · ▶ 1:55

"Finally sub agents in Codex, thank you. They work, which is what I want"

Live Vibe Check · ▶ 8:02

Stripe
Stripe uses

"It has connections to all of our YouTube, our Stripe account, like all that kind of stuff"

Every · ▶ 35:31

"Agent browser CLI from Vercel which is very good. I love that"

Live Vibe Check · ▶ 1:05:22

Claude 3.5 Sonnet

"I'm using two models: Claude 3.5 Sonnet and Codex 5.3. Both high efforts. 50/50 actually"

Live Vibe Check · ▶ 54:00

Opus
Opus uses

"I would still pick Opus 4.6 as a vibe coder"

Every · ▶ 31:55

Mentioned (7)

Codex
Codex "It's a Codex model. It's available now for pro subscribers in the app and in the CLI" ▶ 1:18
Cerebras
Cerebras "It's their first model that's on Cerebras hardware" ▶ 1:34
Composer "Composer was there in the past. The first time I felt excited about a dumber model was Composer" ▶ 2:41
Anthropic
Anthropic "There's a fast mode in Anthropic as well" ▶ 2:45
Claude
Claude "It airs between sub agents and like swarms in Claude" ▶ 8:47
Kora
Kora "I built Kora which is AI's email assistant" ▶ 19:04
Every Growth OS "We have this thing that Austin built called Every Growth OS" ▶ 35:26