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GPT-5.3 Codex Spark: Faster, But You Should Not Reuse gpt-5.3-codex Config

Posted February 13, 2026 by XAI Tech Team ‐ 3Β min read

On February 12, 2026, OpenAI announced GPT-5.3 Codex Spark. If you are already using gpt-5.3-codex, the most important takeaway is:

gpt-5.3-codex-spark is not a "stronger reasoning model"; it is a "faster real-time coding model."

Official Positioning of GPT-5.3 Codex Spark

Based on OpenAI's latest announcement and the Codex changelog, Spark is positioned as:

  1. Low-latency, smaller coding model for real-time collaboration: best for short loops and immediate feedback.
  2. Very high generation speed: OpenAI reports up to 1000+ tokens/s on simple coding tasks, with first-token latency often around 200-400ms.
  3. Strong fit for one-shot editing: ideal for quick fixes and focused code changes.
  4. Text-only (for now): explicitly described as "text-only for now".

Key Differences vs gpt-5.3-codex (Configuration View)

Itemgpt-5.3-codexgpt-5.3-codex-spark
Model focusComplex tasks, long coding/execution chainsReal-time collaboration, fast small edits, low latency
reasoning paramsCan be configured when neededNot supported (do not configure)
Multimodal inputDepends on model/product entrypointNot supported; use text-only requests
Typical use casesLarge task decomposition, complex refactors, long sessionsQuick patches, function-level edits, instant coding Q&A
Important (Codex Client)
When switching to gpt-5.3-codex-spark, do not keep the reasoning settings used for gpt-5.3-codex.
Specifically, remove or do not set: model_reasoning_effort and model_reasoning_summary.

Codex Client Config Examples

1) gpt-5.3-codex (reasoning can be enabled)

model_provider = "xai"
model = "gpt-5.3-codex"
model_reasoning_effort = "high"
model_reasoning_summary = "detailed"

[model_providers.xai]
name = "xai"
base_url = "https://api.xairouter.com"
wire_api = "responses"
requires_openai_auth = false
env_key = "OPENAI_API_KEY"

2) gpt-5.3-codex-spark (do not configure reasoning)

model_provider = "xai"
model = "gpt-5.3-codex-spark"
# Spark does not support reasoning fields
# model_reasoning_effort = "high"
# model_reasoning_summary = "detailed"

[model_providers.xai]
name = "xai"
base_url = "https://api.xairouter.com"
wire_api = "responses"
requires_openai_auth = false
env_key = "OPENAI_API_KEY"

API Usage Notes

  1. Switch model id to: gpt-5.3-codex-spark
  2. Keep inputs text-only; do not send image/audio as Spark's standard input mode
  3. Break tasks into smaller steps; Spark is best for fast iterative loops rather than long single-pass reasoning

Conclusion

If your priority is fast feedback and high interaction frequency, Spark is a strong choice. If you need heavy planning, deep reasoning, and long multi-step execution, gpt-5.3-codex remains the safer default.

References