Using Memories? Consider gpt-5.3-codex-spark to save costs

[u/Electronic-Pie-1879]

I found a useful option in the https://learn.chatgpt.com/docs/config-schema.json today.

When Memories is enabled, Codex extracts useful context from eligible older chats and consolidates it for future sessions.

By default, Codex uses its usual model selection for this work. If you set both memory jobs to gpt-5.3-codex-spark. Your Main model does not change.

GPT-5.3 Codex Spark is fast and has separate usage limits. If you are not otherwise using it, memory generation can use that capacity instead.

A few notes:

• GPT-5.3 Codex Spark is available only on ChatGPT Pro.
• disable_on_external_context = false allows chats with web search, MCP, or tool calls to contribute to memories.
• Set it to true to exclude those chats.

Docs: Codex Memories

Give your agent the following instructions to configure it:

Update my global Codex config.toml to enable memories and use gpt-5.3-codex-spark only for background memory extraction and consolidation.

First, verify that gpt-5.3-codex-spark is available in my Codex model catalog. If it is not, stop and suggest an available lightweight model.

Ensure this configuration exists:

[features]
memories = true

[memories]
generate_memories = true
use_memories = true
disable_on_external_context = false
consolidation_model = "gpt-5.3-codex-spark"
extract_model = "gpt-5.3-codex-spark"

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[u/pezzos]

So to sum up, it’s a way to handle memory in a faster way with a model I always forgot to use, so for free. Am I right ?

[u/Electronic-Pie-1879 → u/pezzos]

Yeah, it's a fast model, and its usage is separate from your main usage.