Codex Models

comparisonintermediate8 min readVerified Mar 8, 2026

Compare GPT-5.4, GPT-5.3-Codex, and GPT-5.3-Codex-Spark: capabilities, context windows, pricing, and which model to use for which task.

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Codex Models

Codex supports multiple models optimized for different coding tasks. This guide helps you choose the right model for your workflow.

Model Overview#

| Model | Context | Best For | Availability | |-------|---------|----------|-------------| | GPT-5.4 | 1M (experimental) | Mixed workflows, recommended default | All plans | | GPT-5.3-Codex | 400K+ | Pure coding, intensive programming | All plans | | GPT-5.3-Codex-Spark | 128K | Quick edits, rapid prototyping | Pro plan (research preview) | | GPT-5.2-Codex | 200K | CI/CD code review (still recommended for review pipelines) | API |

GPT-5.4: The Recommended Default#

GPT-5.4 is OpenAI's unified flagship model. It combines coding, reasoning, tool use, and computer control in one model.

Strengths#

  • 47% fewer reasoning tokens than GPT-5.3-Codex for tool-heavy workflows
  • Native computer use — Can operate browsers and desktop applications
  • Strongest general reasoning — Best for tasks that mix code with planning
  • 1M context window (experimental) — Handle massive codebases

When to Use It#

  • Your default model for most Codex tasks
  • Mixed workflows involving code + reasoning + tools
  • Tasks that require understanding context beyond just code
  • Agent workflows with frequent tool calls
# ~/.codex/config.toml
model = "gpt-5.4"

GPT-5.3-Codex: The Coding Specialist#

GPT-5.3-Codex is optimized specifically for software engineering. It was trained on complex, real-world engineering tasks.

Strengths#

  • State-of-the-art SWE-Bench Pro — Spans four programming languages
  • Terminal-Bench 2.0 leader at 77.3% — Best for terminal/DevOps work
  • 25% faster than its predecessor (GPT-5.2-Codex)
  • More cost-effective for pure coding than GPT-5.4
  • 400K+ context window — Handles large codebases

When to Use It#

  • Intensive programming tasks (feature development, refactoring)
  • Terminal-native workflows (DevOps, scripting, CLI tools)
  • Budget-sensitive projects (lower per-token cost)
  • Code review (set as review_model)
model = "gpt-5.3-codex"
# Or set just for review
review_model = "gpt-5.3-codex"

Benchmarks#

| Benchmark | GPT-5.3-Codex | GPT-5.4 | |-----------|---------------|---------| | SWE-Bench Pro | 56.8% | Comparable | | Terminal-Bench 2.0 | 77.3% | Lower | | Token efficiency | Baseline | 47% fewer on tool-heavy tasks |

GPT-5.3-Codex-Spark: The Speed Demon#

Spark is a distilled, Cerebras-accelerated variant designed for near-instant responses at over 1,000 tokens per second.

Strengths#

  • 15x faster generation than standard GPT-5.3-Codex
  • Near-instant responses — Keeps you in flow
  • Great for small tasks — Quick edits, fixes, explanations
  • Powered by Cerebras — Ultra-low latency hardware

Limitations#

Warning

Spark is not a replacement for GPT-5.3-Codex. It trades reasoning depth for speed:

  • 128K context (vs 400K+ for full model)
  • Weaker on multi-step reasoning and complex debugging
  • Known hallucination issues — Fabricated API endpoints, phantom packages
  • Terminal-Bench estimate ~58.4% (vs 77.3% for full model)
  • Unreliable structured output in some cases
### When to Use It
  • Quick explanations and code snippets
  • Simple bug fixes with clear errors
  • Rapid prototyping iterations
  • Tasks where speed matters more than depth
model = "gpt-5.3-codex-spark"

Model Selection Guide#

| Task Type | Recommended Model | Why | |-----------|-------------------|-----| | Daily development | GPT-5.4 | Best all-around | | Complex feature | GPT-5.3-Codex | Strongest coding | | Quick fix | GPT-5.3-Codex-Spark | Fastest response | | Code review | GPT-5.3-Codex | Best accuracy | | DevOps/terminal work | GPT-5.3-Codex | Terminal-Bench leader | | Mixed code + reasoning | GPT-5.4 | Unified capabilities | | Budget-conscious work | GPT-5.3-Codex | Lower per-token cost | | CI/CD pipelines | GPT-5.2-Codex or GPT-5.3-Codex | Reliable, cost-effective |

API Pricing#

| Model | Input (per 1M tokens) | Output (per 1M tokens) | Caching Discount | |-------|----------------------|----------------------|-----------------| | GPT-5.4 | $1.25 | $10.00 | — | | GPT-5.3-Codex | $1.50 | $6.00 | 75% prompt caching |

Tip

GPT-5.3-Codex's 75% prompt caching discount makes it significantly cheaper for repetitive tasks like CI/CD reviews where the same codebase context is sent repeatedly.

## Switching Models

In config.toml#

model = "gpt-5.4"                    # Default model
review_model = "gpt-5.3-codex"      # Review-specific model

At the Command Line#

codex -c model="gpt-5.3-codex" "Refactor the auth module"

In the TUI#

Use the /model slash command to switch models during a session.

Per-Profile#

[profiles.deep-work]
model = "gpt-5.3-codex"
model_reasoning_effort = "high"

[profiles.quick-tasks]
model = "gpt-5.3-codex-spark"

The Evolution of Codex Models#

| Release | Model | Key Improvement | |---------|-------|-----------------| | Dec 2025 | GPT-5.2-Codex | Strong agentic coding | | Feb 2026 | GPT-5.3-Codex | 25% faster, SOTA SWE-bench Pro | | Feb 2026 | GPT-5.3-Codex-Spark | 15x speed via Cerebras partnership | | Mar 2026 | GPT-5.4 | Unified coding + reasoning + computer use |

Next Steps#

PreviousUI PrototypingNextMulti-Agent Workflows