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
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.