Model comparison
GPT-5.2 Codex vs GPT-5 Nano
GPT-5.2 Codex is the stronger model overall, scoring 42.2 to 33.4 on the Noometry Index. GPT-5 Nano costs 35× less per token, which makes it the better buy when GPT-5.2 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-5.2 Codex scores higher in 2 categories and GPT-5 Nano in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.2 Codex leads 40.7 to 25.6.
- The biggest single-benchmark swing is Terminal-Bench: 66.5% for GPT-5.2 Codex and 21.8% for GPT-5 Nano.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
Side by side
| GPT-5.2 Codex | GPT-5 Nano | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 42.2 | 33.4 |
| Released | 2025-12-18 | 2025-08-07 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 400K |
| Max output | 128K | 128K |
| Input $ / M tokens | $1.75 | $0.05 |
| Output $ / M tokens | $14 | $0.40 |
| Results tracked | 5 | 48 |
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Category by category
Coding GPT-5.2 Codex leads
GPT-5.2 Codex: 45.4 (#66), GPT-5 Nano: 33.3 (#248)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| SWE-bench Verified (bash only) | 72.8% | 34.8% |
| ALE-Bench | 1,300 | 718.67 |
| LMArena WebDev | 1339 | — |
| SWE-bench Multilingual | 66.3% | — |
| WeirdML | — | 38.1% |
| LMArena Coding | — | 1351 |
Agentic & Tool Use GPT-5.2 Codex leads
GPT-5.2 Codex: 40.7 (#20), GPT-5 Nano: 25.6 (#99)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| Terminal-Bench | 66.5% | 21.8% |
| Berkeley Function Calling Leaderboard | — | 51.5% |
Reasoning Not comparable
GPT-5.2 Codex: —, GPT-5 Nano: 16.4 (#291)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| ARC-AGI-2 | — | 2.6% |
| Kagi LLM Benchmark | — | 62.2% |
| ARC-AGI-1 | — | 20.7% |
| Chess Puzzles | — | 27% |
| LMArena Hard Prompts | — | 1329 |
| Mystery Game Puzzles | — | 9% |
| DTBench | — | 62.7% |
| LMCA | — | 7.9% |
| Epoch Capabilities Index | — | 139.39 |
| ForecastBench | — | 59.1 |
Math Not comparable
GPT-5.2 Codex: —, GPT-5 Nano: 29.1 (#221)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 20% |
| FrontierMath Tier 4 | — | 2.4% |
| OTIS Mock AIME 2024-2025 | — | 81.1% |
| ProofBench | — | 12% |
| Omni-MATH | — | 54.6% |
| LMArena Math | — | 1318 |
| MATH Level 5 | — | 95.2% |
| FrontierMath (Feb 2025 set) | — | 8.3% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Not comparable
GPT-5.2 Codex: —, GPT-5 Nano: 35.8 (#166)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| GPQA Diamond | — | 69.4% |
| SimpleQA Verified | — | 11.7% |
| MMLU-Pro | — | 77.8% |
| Vectara Hallucination Rate | — | 10.5% |
| GPQA (HELM) | — | 67.9% |
| LMArena Expert | — | 1321 |
Multimodal Not comparable
GPT-5.2 Codex: —, GPT-5 Nano: 30.7 (#102)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| LMArena Vision | — | 1159 |
| VPCT | — | 37.2% |
Multilingual Not comparable
GPT-5.2 Codex: —, GPT-5 Nano: 45.5 (#167)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| LMArena Non-English | — | 1313 |
| LMArena Chinese | — | 1355 |
| LMArena German | — | 1329 |
| LMArena Korean | — | 1269 |
| LMArena Russian | — | 1296 |
| LMArena Spanish | — | 1360 |
Instruction Following Not comparable
GPT-5.2 Codex: —, GPT-5 Nano: 75.2 (#72)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| IFEval | — | 93.2% |
| LMArena Instruction Following | — | 1306 |
Long Context Not comparable
GPT-5.2 Codex: —, GPT-5 Nano: 31.3 (#275)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| Fiction.LiveBench | — | 44.4% |
| LMArena Longer Query | — | 1313 |
Writing & Preference Not comparable
GPT-5.2 Codex: —, GPT-5 Nano: 39.4 (#244)
| Benchmark | GPT-5.2 Codex | GPT-5 Nano |
|---|---|---|
| LMArena Text | — | 1320 |
| LMArena Creative Writing | — | 1250 |
| EQ-Bench Creative Writing | — | 705 |
| WildBench | — | 80.6% |
| LMArena Multi-Turn | — | 1311 |
Frequently asked questions
Is GPT-5.2 Codex better than GPT-5 Nano?
GPT-5.2 Codex is the stronger model overall, scoring 42.2 to 33.4 on the Noometry Index. GPT-5 Nano costs 35× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.
Which is cheaper, GPT-5.2 Codex or GPT-5 Nano?
GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.
Is GPT-5.2 Codex or GPT-5 Nano better for coding?
GPT-5.2 Codex scores higher on coding benchmarks: 45.4 versus 33.3 in the Noometry coding category.
Which has the bigger context window?
Both accept 400K tokens.
How many benchmarks do GPT-5.2 Codex and GPT-5 Nano share?
3 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and GPT-5 Nano has 48.