Model comparison
GPT-5.3 Chat vs GPT-5.3 Codex
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 42.8 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in coding, where GPT-5.3 Codex leads 48.6 to 41.4.
- Both cost about the same: $1.75 input and $14 output per million tokens.
- GPT-5.3 Codex accepts more context: 400K tokens versus 128K.
Side by side
| GPT-5.3 Chat | GPT-5.3 Codex | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 42.8 | 45.8 |
| Released | 2026-03-03 | 2026-02-05 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | 400K |
| Max output | 16K | 128K |
| Input $ / M tokens | $1.75 | $1.75 |
| Output $ / M tokens | $14 | $14 |
| Results tracked | 18 | 8 |
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Category by category
Coding GPT-5.3 Codex leads
GPT-5.3 Chat: 41.4 (#124), GPT-5.3 Codex: 48.6 (#56)
| Benchmark | GPT-5.3 Chat | GPT-5.3 Codex |
|---|---|---|
| SWE-bench Verified | — | 74.8% |
| LMArena WebDev | — | 1409 |
| WeirdML | — | 79.3% |
| LMArena Coding | 1408 | — |
| ALE-Bench | — | 1,655 |
Agentic & Tool Use Not comparable
GPT-5.3 Chat: —, GPT-5.3 Codex: 48.0 (#9)
| Benchmark | GPT-5.3 Chat | GPT-5.3 Codex |
|---|---|---|
| Terminal-Bench | — | 78.4% |
| METR Time Horizons | — | 74.5% |
| Vending-Bench 2 | — | 5,940 |
Reasoning Not comparable
GPT-5.3 Chat: 28.5 (#102), GPT-5.3 Codex: —
| Benchmark | GPT-5.3 Chat | GPT-5.3 Codex |
|---|---|---|
| LMArena Hard Prompts | 1399 | — |
| Epoch Capabilities Index | — | 156.77 |
Math Not comparable
GPT-5.3 Chat: 38.2 (#142), GPT-5.3 Codex: —
| Benchmark | GPT-5.3 Chat | GPT-5.3 Codex |
|---|---|---|
| LMArena Math | 1389 | — |
Knowledge Not comparable
GPT-5.3 Chat: 38.8 (#140), GPT-5.3 Codex: —
| Benchmark | GPT-5.3 Chat | GPT-5.3 Codex |
|---|---|---|
| LMArena Expert | 1397 | — |
Multilingual Not comparable
GPT-5.3 Chat: 50.3 (#124), GPT-5.3 Codex: —
| Benchmark | GPT-5.3 Chat | GPT-5.3 Codex |
|---|---|---|
| LMArena Non-English | 1382 | — |
| LMArena Chinese | 1432 | — |
| LMArena French | 1397 | — |
| LMArena German | 1384 | — |
| LMArena Japanese | 1352 | — |
| LMArena Korean | 1346 | — |
| LMArena Russian | 1400 | — |
| LMArena Spanish | 1371 | — |
Instruction Following Not comparable
GPT-5.3 Chat: 72.8 (#129), GPT-5.3 Codex: —
| Benchmark | GPT-5.3 Chat | GPT-5.3 Codex |
|---|---|---|
| LMArena Instruction Following | 1378 | — |
Long Context Not comparable
GPT-5.3 Chat: 42.6 (#120), GPT-5.3 Codex: —
| Benchmark | GPT-5.3 Chat | GPT-5.3 Codex |
|---|---|---|
| LMArena Longer Query | 1396 | — |
Writing & Preference Not comparable
GPT-5.3 Chat: 63.1 (#68), GPT-5.3 Codex: —
| Benchmark | GPT-5.3 Chat | GPT-5.3 Codex |
|---|---|---|
| LMArena Text | 1389 | — |
| LMArena Creative Writing | 1355 | — |
| EQ-Bench Creative Writing | 1690 | — |
| LMArena Multi-Turn | 1412 | — |
Frequently asked questions
Is GPT-5.3 Chat better than GPT-5.3 Codex?
GPT-5.3 Codex is the stronger model overall, scoring 45.8 to 42.8 on the Noometry Index.
Which is cheaper, GPT-5.3 Chat or GPT-5.3 Codex?
GPT-5.3 Codex is cheaper. It lists at $1.75 per million input tokens and $14 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.
Is GPT-5.3 Chat or GPT-5.3 Codex better for coding?
GPT-5.3 Codex scores higher on coding benchmarks: 48.6 versus 41.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5.3 Codex does, with 400K tokens against 128K.
How many benchmarks do GPT-5.3 Chat and GPT-5.3 Codex share?
0 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and GPT-5.3 Codex has 8.