Model comparison
GPT-5.3 Codex vs GPT-5.4 nano
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.3 Codex #26 (Supported); GPT-5.4 nano #25 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.3 Codex and GPT-5.4 nano share 15 comparable benchmark results. 1 of 8 categories are comparable. 6 results are unique to GPT-5.3 Codex; 14 to GPT-5.4 nano.
Updated July 23, 2026- Shared results
- 15
- GPT-5.3 Codex only
- 6
- GPT-5.4 nano only
- 14
- Comparable categories
- 1 / 8
Pick GPT-5.4 nano if you want the stronger benchmark profile. GPT-5.3 Codex only becomes the better choice if agentic is the priority.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.4 nano has the cleaner BenchAlign overall profile here, landing at 66.79 versus 66.69. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-5.3 Codex is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.20 input / $1.25 output per 1M tokens for GPT-5.4 nano. That is roughly 11.2x on output cost alone.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-5.3 Codex | Δ | GPT-5.4 nano |
|---|---|---|---|
| Agentic | GPT-5.3 Codex71.4 | Margin← 28.5 | GPT-5.4 nano42.9 |
| Coding | GPT-5.3 Codex67.2 | MarginNo overlap | GPT-5.4 nanoNot measured |
| Knowledge | GPT-5.3 CodexNot measured | MarginNo overlap | GPT-5.4 nano43.8 |
| Math | GPT-5.3 CodexNot measured | MarginNo overlap | GPT-5.4 nano21.0 |
| Multimodal | GPT-5.3 CodexNot measured | MarginNo overlap | GPT-5.4 nano66.1 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 77.3%B 46.3%Winner: GPT-5.3 CodexΔ 31Terminal-Bench 2.0: GPT-5.3 Codex scored 77.3%; GPT-5.4 nano scored 46.3%. GPT-5.3 Codex wins this benchmark. - Source ↗
OSWorld-Verified
AgenticA 64.7%B 39%Winner: GPT-5.3 CodexΔ 25.7OSWorld-Verified: GPT-5.3 Codex scored 64.7%; GPT-5.4 nano scored 39%. GPT-5.3 Codex wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.3 Codex | GPT-5.4 nano | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.3 Codex$1.75 input / $14 output | GPT-5.4 nano$0.2 input / $1.25 output | GPT-5.4 nano has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.3 Codex79 tok/s | GPT-5.4 nano191 tok/s | GPT-5.4 nano has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-5.3 Codex88.26 s | GPT-5.4 nano3.64 s | GPT-5.4 nano reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-5.3 Codex400K | GPT-5.4 nano400K | Listed context windows are equal. |
Benchmark Deep Dive
AgenticGPT-5.3 Codex wins11 benchmarks
| Benchmark | GPT-5.3 Codex | GPT-5.4 nano | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 77.3% | 46.3% | GPT-5.3 Codex leads |
| OSWorld-VerifiedSource | 64.7% | 39% | GPT-5.3 Codex leads |
| τ²-bench resultsSource | 86% | 76% | GPT-5.3 Codex leads |
| Gert LabsSource | 57.47% | — | Not comparable |
| JobBenchSource | 33.7% | — | Not comparable |
| MCP AtlasSource | — | 56.1% | Not comparable |
| ToolathlonSource | — | 35.5% | Not comparable |
| AA Agentic IndexSource | — | 27.5% | Not comparable |
| APEX-Agents-AASource | — | 24.9% | Not comparable |
| GDPval-AASource | — | 30.0% | Not comparable |
| GDPval-AASource | — | 1100 | Not comparable |
Coding6 benchmarks
| Benchmark | GPT-5.3 Codex | GPT-5.4 nano | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 85% | — | Not comparable |
| SWE-bench ProSource | 56.8% | — | Not comparable |
| SWE-RebenchSource | 58.2% | — | Not comparable |
| Vibe Code BenchSource | 61.77% | 26.10% | GPT-5.3 Codex leads |
| AA-SciCodeSource | 53.2% | 46.9% | GPT-5.3 Codex leads |
| AA Coding IndexSource | — | 56.1% | Not comparable |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | GPT-5.3 Codex | GPT-5.4 nano | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 44.3% | 38.2% | GPT-5.3 Codex leads |
| AA-GPQA DiamondSource | 91.5% | 81.7% | GPT-5.3 Codex leads |
| AA-HLESource | 39.9% | 26.5% | GPT-5.3 Codex leads |
| AA-Omniscience IndexSource | 9.9% | -29.5% | GPT-5.3 Codex leads |
| AA-Omniscience AccuracySource | 51.8% | 25.4% | GPT-5.3 Codex leads |
| AA-Omniscience Hallucination RateSource | 86.9% | 73.6% | GPT-5.4 nano leads |
| GPQASource | — | 82.8% | Not comparable |
| HLESource | — | 37.7% | Not comparable |
| HLE w/o toolsSource | — | 24.3% | Not comparable |
Math2 benchmarks
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.3 Codex | GPT-5.4 nano | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | 75.9% | GPT-5.4 nano leads |
Frequently Asked Questions (2)
Which is better, GPT-5.3 Codex or GPT-5.4 nano?
GPT-5.4 nano is ahead on BenchLM's BenchAlign leaderboard, 66.79 to 66.69. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 77.3% and 46.3%.
Which is better for agentic tasks, GPT-5.3 Codex or GPT-5.4 nano?
GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 71.4 versus 42.9. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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