Model comparison
GPT-5.3 Chat vs o3-mini
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 36.7 on the Noometry Index. o3-mini costs 2.5× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Summary
- They share 17 benchmarks with published results for both. GPT-5.3 Chat scores higher in 7 categories and o3-mini in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-5.3 Chat leads 63.1 to 50.3.
- o3-mini is cheaper at $1.10 / $4.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
- o3-mini accepts more context: 200K tokens versus 128K.
Side by side
| GPT-5.3 Chat | o3-mini | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 42.8 | 36.7 |
| Released | 2026-03-03 | 2024-12-20 |
| Weights | Proprietary | Proprietary |
| Context window | 128K | 200K |
| Max output | 16K | 100K |
| Input $ / M tokens | $1.75 | $1.10 |
| Output $ / M tokens | $14 | $4.40 |
| Results tracked | 18 | 51 |
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Category by category
Coding Too close to call
GPT-5.3 Chat: 41.4 (#124), o3-mini: 40.8 (#132)
| Benchmark | GPT-5.3 Chat | o3-mini |
|---|---|---|
| LMArena Coding | 1408 | 1378 |
| Aider Polyglot | — | 60.4% |
| SciCode | — | 39.8% |
| GSO | — | 1.3% |
| WeirdML | — | 43.7% |
| LiveBench Coding | — | 82.7% |
| CadEval | — | 54% |
Agentic & Tool Use Not comparable
GPT-5.3 Chat: —, o3-mini: 29.6 (#84)
| Benchmark | GPT-5.3 Chat | o3-mini |
|---|---|---|
| Cybench | — | 22.5% |
Reasoning GPT-5.3 Chat leads
GPT-5.3 Chat: 28.5 (#102), o3-mini: 16.3 (#305)
| Benchmark | GPT-5.3 Chat | o3-mini |
|---|---|---|
| LMArena Hard Prompts | 1399 | 1366 |
| ARC-AGI-2 | — | 3% |
| SimpleBench | — | 22.8% |
| ARC-AGI-1 | — | 34.5% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 17% |
| LiveBench Reasoning | — | 89.6% |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 68.8% |
| LiveBench Data Analysis | — | 70.6% |
| LMCA | — | 19% |
| Epoch Capabilities Index | — | 140.34 |
| ForecastBench | — | 59.6 |
| LiveBench | — | 75.9% |
Math GPT-5.3 Chat leads
GPT-5.3 Chat: 38.2 (#142), o3-mini: 28.1 (#244)
| Benchmark | GPT-5.3 Chat | o3-mini |
|---|---|---|
| LMArena Math | 1389 | 1396 |
| FrontierMath (Tiers 1-3) | — | 18.6% |
| FrontierMath Tier 4 | — | 0% |
| OTIS Mock AIME 2024-2025 | — | 76.9% |
| LiveBench Math | — | 77.3% |
| MATH Level 5 | — | 96.5% |
| FrontierMath (Feb 2025 set) | — | 12.4% |
| FrontierMath Tier 4 (v1) | — | 4.2% |
Knowledge Too close to call
GPT-5.3 Chat: 38.8 (#140), o3-mini: 38.3 (#146)
| Benchmark | GPT-5.3 Chat | o3-mini |
|---|---|---|
| LMArena Expert | 1397 | 1364 |
| GPQA Diamond | — | 77% |
| SimpleQA Verified | — | 15.3% |
| Confabulations | — | 17.9% |
Multilingual GPT-5.3 Chat leads
GPT-5.3 Chat: 50.3 (#124), o3-mini: 45.7 (#164)
| Benchmark | GPT-5.3 Chat | o3-mini |
|---|---|---|
| LMArena Non-English | 1382 | 1319 |
| LMArena Chinese | 1432 | 1379 |
| LMArena French | 1397 | 1334 |
| LMArena German | 1384 | 1303 |
| LMArena Japanese | 1352 | 1286 |
| LMArena Korean | 1346 | 1314 |
| LMArena Russian | 1400 | 1304 |
| LMArena Spanish | 1371 | 1321 |
Instruction Following o3-mini leads
GPT-5.3 Chat: 72.8 (#129), o3-mini: 75.1 (#72)
| Benchmark | GPT-5.3 Chat | o3-mini |
|---|---|---|
| LMArena Instruction Following | 1378 | 1337 |
| LiveBench Instruction Following | — | 84.4% |
Long Context GPT-5.3 Chat leads
GPT-5.3 Chat: 42.6 (#120), o3-mini: 33.8 (#256)
| Benchmark | GPT-5.3 Chat | o3-mini |
|---|---|---|
| LMArena Longer Query | 1396 | 1343 |
| Fiction.LiveBench | — | 50% |
Writing & Preference GPT-5.3 Chat leads
GPT-5.3 Chat: 63.1 (#68), o3-mini: 50.3 (#182)
| Benchmark | GPT-5.3 Chat | o3-mini |
|---|---|---|
| LMArena Text | 1389 | 1337 |
| LMArena Creative Writing | 1355 | 1286 |
| LMArena Multi-Turn | 1412 | 1320 |
| Short-Story Creative Writing | — | 61.7% |
| EQ-Bench Creative Writing | 1690 | — |
| LiveBench Language | — | 50.7% |
Frequently asked questions
Is GPT-5.3 Chat better than o3-mini?
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 36.7 on the Noometry Index. o3-mini costs 2.5× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.
Which is cheaper, GPT-5.3 Chat or o3-mini?
o3-mini is cheaper. It lists at $1.10 per million input tokens and $4.40 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.
Is GPT-5.3 Chat or o3-mini better for coding?
They score almost the same on coding (41.4 vs 40.8); test both on your own repository before choosing.
Which has the bigger context window?
o3-mini does, with 200K tokens against 128K.
How many benchmarks do GPT-5.3 Chat and o3-mini share?
17 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and o3-mini has 51.