First thoughts using gpt-5.3-codex-spark in Codex CLI:

Blazing fast but it definitely has a small model feel.

It's tearing up bluey bench (my personal agent speed benchmark), which is a file system benchmark where I have the agent generate transcripts for untitled episodes of a season of bluey, perform a web search to find the episode descriptions, and then match the transcripts against the descriptions to generate file names and metadata for each episode.

Downsides:

- It has to be prompted to do actions in my media library AGENTS.md that the larger models adhere to without additional prompting.

- It's less careful with how it handles context which means that its actions are less context efficient. Combine that with the smaller context window and I'm seeing frequent compactions.

  Bluey Bench* (minus transcription time):

  Codex CLI
  gpt-5.3-codex-spark low        20s
  gpt-5.3-codex-spark medium     41s
  gpt-5.3-codex-spark xhigh   1m 09s (1 compaction)

  gpt-5.3-codex low           1m 04s
  gpt-5.3-codex medium        1m 50s

  gpt-5.2 low                 3m 04s
  gpt-5.2 medium              5m 20s

  Claude Code
  opus-4.6 (no thinking)      1m 04s

  Antigravity
  gemini-3-flash              1m 40s
  gemini-3-pro low            3m 39s

  *Season 2, 52 episodes

can we plese make the bluey bench the gold standard for all models always

Can you compare it to Opus 4.6 with thinking disabled? It seems to have very impressive benchmark scores. Could also be pretty fast.

I wonder why they named it so similiarly to the normal codex model while it much worse, while cool of course.