Model comparison
GPT-3.5-turbo vs GPT-5.3 Codex
GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 23.1 on the Noometry Index. GPT-3.5-turbo costs 6.4× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Summary
- They share 3 benchmarks with published results for both. GPT-3.5-turbo scores higher in 0 categories and GPT-5.3 Codex in 1 category; one gap is clear of the uncertainty.
- The widest gap is in coding, where GPT-5.3 Codex leads 48.5 to 23.5.
- The biggest single-benchmark swing is WeirdML: 3.5% for GPT-3.5-turbo and 79.3% for GPT-5.3 Codex.
- GPT-3.5-turbo is cheaper at $0.50 / $1.50 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 16K.
Side by side
| GPT-3.5-turbo | GPT-5.3 Codex | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 23.1 | 45.5 |
| Released | 2023-03-01 | 2026-02-05 |
| Weights | Proprietary | Proprietary |
| Context window | 16K | 400K |
| Max output | 4K | 128K |
| Input $ / M tokens | $0.50 | $1.75 |
| Output $ / M tokens | $1.50 | $14 |
| Results tracked | 44 | 8 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.3 Codex leads
GPT-3.5-turbo: 23.5 (#326), GPT-5.3 Codex: 48.5 (#51)
| Benchmark | GPT-3.5-turbo | GPT-5.3 Codex |
|---|---|---|
| WeirdML | 3.5% | 79.3% |
| SWE-bench Verified | — | 74.8% |
| LMArena WebDev | — | 1408 |
| BigCodeBench Instruct | 39.1% | — |
| LMArena Coding | 1137 | — |
| BigCodeBench Complete | 50.6% | — |
| ALE-Bench | — | 1,655 |
| HumanEval+ | 70.7% | — |
| MBPP+ | 69.7% | — |
Agentic & Tool Use Not comparable
GPT-3.5-turbo: —, GPT-5.3 Codex: 47.8 (#9)
| Benchmark | GPT-3.5-turbo | GPT-5.3 Codex |
|---|---|---|
| METR Time Horizons | 21.5% | 74.5% |
| Terminal-Bench | — | 78.4% |
| Vending-Bench 2 | — | 5,940 |
Reasoning Not comparable
GPT-3.5-turbo: 13.3 (#328), GPT-5.3 Codex: —
| Benchmark | GPT-3.5-turbo | GPT-5.3 Codex |
|---|---|---|
| Epoch Capabilities Index | 118.48 | 156.84 |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1108 | — |
| Mystery Game Puzzles | 3% | — |
| DTBench | 48.5% | — |
| LMCA | 9.7% | — |
| Adversarial NLI | 58.1% | — |
| BIG-Bench Hard | 61.6% | — |
| CommonsenseQA 2.0 | 57% | — |
| ForecastBench | 50.4 | — |
| WinoGrande | 81.6% | — |
Math Not comparable
GPT-3.5-turbo: 6.0 (#321), GPT-5.3 Codex: —
| Benchmark | GPT-3.5-turbo | GPT-5.3 Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 0% | — |
| OTIS Mock AIME 2024-2025 | 2.2% | — |
| LMArena Math | 1142 | — |
| MATH Level 5 | 15.9% | — |
| GSM8K | 57.8% | — |
Knowledge Not comparable
GPT-3.5-turbo: 10.0 (#298), GPT-5.3 Codex: —
| Benchmark | GPT-3.5-turbo | GPT-5.3 Codex |
|---|---|---|
| GPQA Diamond | 28% | — |
| LMArena Expert | 1070 | — |
| ARC (AI2) Challenge | 87.4% | — |
| BoolQ | 87% | — |
| MMLU | 71.4% | — |
| OpenBookQA | 86% | — |
| TriviaQA | 85.8% | — |
Multilingual Not comparable
GPT-3.5-turbo: 31.6 (#253), GPT-5.3 Codex: —
| Benchmark | GPT-3.5-turbo | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1108 | — |
| LMArena Chinese | 1075 | — |
| LMArena French | 1117 | — |
| LMArena German | 1090 | — |
| LMArena Japanese | 1043 | — |
| LMArena Korean | 1019 | — |
| LMArena Russian | 1123 | — |
| LMArena Spanish | 1120 | — |
Instruction Following Not comparable
GPT-3.5-turbo: 58.1 (#257), GPT-5.3 Codex: —
| Benchmark | GPT-3.5-turbo | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1119 | — |
Long Context Not comparable
GPT-3.5-turbo: 34.0 (#249), GPT-5.3 Codex: —
| Benchmark | GPT-3.5-turbo | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1121 | — |
Writing & Preference Not comparable
GPT-3.5-turbo: 25.4 (#300), GPT-5.3 Codex: —
| Benchmark | GPT-3.5-turbo | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1125 | — |
| LMArena Creative Writing | 1092 | — |
| EQ-Bench Creative Writing | 451 | — |
| LMArena Multi-Turn | 1117 | — |
Frequently asked questions
Is GPT-3.5-turbo better than GPT-5.3 Codex?
GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 23.1 on the Noometry Index. GPT-3.5-turbo costs 6.4× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.
Which is cheaper, GPT-3.5-turbo or GPT-5.3 Codex?
GPT-3.5-turbo is cheaper. It lists at $0.50 per million input tokens and $1.50 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.
Is GPT-3.5-turbo or GPT-5.3 Codex better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.5 versus 23.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5.3 Codex does, with 400K tokens against 16K.
How many benchmarks do GPT-3.5-turbo and GPT-5.3 Codex share?
3 benchmarks have published results for both models. GPT-3.5-turbo has 44 scored results on Noometry and GPT-5.3 Codex has 8.