GPT-5 vs GPT-5.4 Nano
GPT-5.4 Nano leads GPT-5 on coding, 44.8 to 38.8 on the Vibe Coding Index, and GPT-5.4 Nano costs 8.0x less per output token ($1.25 vs $10.00 per million). Updated October 23, 2026; 76 benchmarks have a result for both.
GPT-5 or GPT-5.4 Nano: which to pick
Pick GPT-5.4 Nano for coding: it scores 44.8 on the Vibe Coding Index against 38.8 for GPT-5, though on 2 benchmarks against 3.
Pick GPT-5 for work measured by LiveCodeBench (Vals AI) or WeirdML, where it leads.
- Shared results
- 76
- GPT-5 only
- 41
- GPT-5.4 Nano only
- 9
- Like-for-like categories
- 7 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
GPT-5.4 Nano
GPT-5.4 Nano scores 44.8 against 38.8.
3 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5
GPT-5 leads, 23.0 against 20.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.4 Nano has a AA Agentic Index result, 16.0.
Directional only
Reasoning
GPQA Diamond
GPT-5
GPT-5 leads, 85.6% against 77.5%.
Same board, both measured
Math
AIME
GPT-5
GPT-5 leads, 93.4% against 88.8%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5
GPT-5 leads, 86.5% against 77.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5 has a Design Arena: websites result, 1184.
Directional only
Long documents
Listed context window
No call
Both take 400K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.4 Nano
GPT-5 $0.0063, GPT-5.4 Nano $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.4 Nano
GPT-5 $0.39, GPT-5.4 Nano $0.14.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5 38.8 from 3 benchmarks, GPT-5.4 Nano 44.8 from 2 benchmarks.
- Widest category
- Agentic work, 10.5 points apart on average over 1 shared benchmark.
- Widest single gap
- SimpleQA Verified: GPT-5 50.1% against GPT-5.4 Nano 11.7%, 38.4 points apart on a 0 to 100 scale.
- Output price
- GPT-5 $10.00 against GPT-5.4 Nano $1.25 per million output tokens, 8.0x apart.
- Context window
- Both take 400K tokens.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-5 | Bars | GPT-5.4 Nano | Ties |
|---|---|---|---|---|
| Coding | 4 | 5 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 14 | 1 | ||
| Math | 6 | 1 | ||
| Knowledge | 11 | 1 | ||
| General | 29 | 1 | ||
| All shared boards | 67 | 9 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index45
| Benchmark | GPT-5 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| Aider polyglot | 88.0% | Not measured | Only GPT-5 measured |
| SWE-bench Verified | 74.4% | Not measured | Only GPT-5 measured |
| LMArena WebDev | 1418 | Not measured | Only GPT-5 measured |
| AA Coding Index | 37.8 | 56.1 | GPT-5.4 Nano |
| LiveCodeBench (Vals AI) | 85.9% | 84.0% | GPT-5 |
| SWE-bench Verified (Vals AI) | 69.0% | 69.8% | GPT-5.4 Nano |
| Vibe Code Bench (Vals AI) | 20.1% | 26.1% | GPT-5.4 Nano |
| Code migration (Vals AI) | Not measured | 14.5% | Only GPT-5.4 Nano measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 41.6% | Only GPT-5.4 Nano measured |
| LiveCodeBench (Artificial Analysis run) | 84.6% | Not measured | Only GPT-5 measured |
| SciCode | Not measured | 47.2% | Only GPT-5.4 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.9% | 42.4% | GPT-5.4 Nano |
| Terminal-Bench | 49.6% | Not measured | Only GPT-5 measured |
| GSO-Bench | 6.9% | Not measured | Only GPT-5 measured |
| WeirdML | 60.7% | 49.2% | GPT-5 |
| ALE-Bench | 807.6 | 1004.5 | GPT-5.4 Nano |
| LMArena Text: coding | 1436 | 1405 | GPT-5 |
| LMArena Text: software and IT | 1420 | 1403 | GPT-5 |
| LMArena WebDev: HTML | 1426 | Not measured | Only GPT-5 measured |
| SciCode | 0.0% | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.0 | 20.7 | GPT-5 |
| Epoch Capabilities Index | 150.0 | 146.0 | GPT-5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 16.0 | Only GPT-5.4 Nano measured |
| Finance Agent (Vals AI) | Not measured | 38.2% | Only GPT-5.4 Nano measured |
| Tax Agent Bench (Vals AI) | Not measured | 5.0% | Only GPT-5.4 Nano measured |
| Legal Research Bench (Vals AI) | Not measured | 6.3% | Only GPT-5.4 Nano measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 44.8% | Only GPT-5.4 Nano measured |
| τ²-Bench Telecom | 86.5% | 76.0% | GPT-5 |
| METR time horizons | 69.6% | Not measured | Only GPT-5 measured |
| Remote Labor Index | 1.7% | Not measured | Only GPT-5 measured |
| GDPval | 34.8% | Not measured | Only GPT-5 measured |
| BALROG | 32.8% | Not measured | Only GPT-5 measured |
| DeepResearch Bench | 49.6% | Not measured | Only GPT-5 measured |
| BrowseComp-Plus | 80.0% | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index141
| Benchmark | GPT-5 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| GPQA Diamond | 85.6% | 77.5% | GPT-5 |
| MMMU Pro (Vals AI) | 81.5% | 73.6% | GPT-5 |
| GPQA Diamond (Artificial Analysis run) | 85.4% | 81.7% | GPT-5 |
| Humanity's Last Exam (Artificial Analysis run) | 28.5% | 28.3% | GPT-5 |
| GPQA Diamond (Epoch AI run) | 86.2% | 78.5% | GPT-5 |
| ARC-AGI | 65.7% | 51.5% | GPT-5 |
| ARC-AGI-2 | 9.9% | 5.7% | GPT-5 |
| SimpleBench | 56.7% | Not measured | Only GPT-5 measured |
| Chess puzzles | 36.0% | 45.0% | GPT-5.4 Nano |
| Mystery game puzzles | 23.0% | 9.0% | GPT-5 |
| EBR-bench | 12.7% | Not measured | Only GPT-5 measured |
| VPCT | 66.0% | Not measured | Only GPT-5 measured |
| LMArena Text: hard prompts | 1415 | 1381 | GPT-5 |
| LMArena Text: expert | 1419 | 1396 | GPT-5 |
| LMArena Text: hard prompts in English | 1419 | 1387 | GPT-5 |
| LMArena Vision: diagrams | 1252 | 1210 | GPT-5 |
| LMArena Vision: homework | 1278 | 1225 | GPT-5 |
| Kagi LLM Benchmark | 72.7% | 39.7% | GPT-5 |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index61
| Benchmark | GPT-5 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| AIME | 93.4% | 88.8% | GPT-5 |
| MATH 500 (Vals AI) | 96.0% | Not measured | Only GPT-5 measured |
| MGSM (Vals AI) | 92.8% | Not measured | Only GPT-5 measured |
| AA Math Index | 94.3 | Not measured | Only GPT-5 measured |
| AIME 2025 (Artificial Analysis run) | 94.3% | Not measured | Only GPT-5 measured |
| OTIS Mock AIME | 91.4% | 87.8% | GPT-5 |
| FrontierMath, tiers 1 to 3 | 55.4% | 44.9% | GPT-5 |
| FrontierMath, tier 4 | 22.0% | 12.2% | GPT-5 |
| ProofBench | 18.0% | 5.0% | GPT-5 |
| MATH level 5 | 98.1% | Not measured | Only GPT-5 measured |
| LMArena Text: math | 1407 | 1406 | GPT-5 |
| LMArena Text: mathematical work | 1405 | 1409 | GPT-5.4 Nano |
| MathArena | 17.1% | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index111
| Benchmark | GPT-5 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| MMLU Pro | 86.5% | 77.2% | GPT-5 |
| LegalBench (Vals AI) | 86.0% | 77.9% | GPT-5 |
| CaseLaw (Vals AI) | 66.5% | 51.9% | GPT-5 |
| CorpFin (Vals AI) | 61.1% | 61.2% | GPT-5.4 Nano |
| TaxEval (Vals AI) | 73.4% | 67.4% | GPT-5 |
| MortgageTax (Vals AI) | 65.5% | 59.1% | GPT-5 |
| MedQA (Vals AI) | 96.3% | Not measured | Only GPT-5 measured |
| MedCode (Vals AI) | 49.6% | 41.0% | GPT-5 |
| MMLU Pro (Artificial Analysis run) | 87.1% | Not measured | Only GPT-5 measured |
| SimpleQA Verified | 50.1% | 11.7% | GPT-5 |
| GeoBench | 81.0% | Not measured | Only GPT-5 measured |
| LMArena Text: science | 1416 | 1374 | GPT-5 |
| LMArena Text: medicine and healthcare | 1413 | 1369 | GPT-5 |
| LMArena Text: legal and government | 1431 | 1368 | GPT-5 |
| LMArena Text: business and finance | 1399 | 1366 | GPT-5 |
| FACTS Benchmark Suite | 56.5% | Not measured | Only GPT-5 measured |
| PRBench Finance | 51.3% | Not measured | Only GPT-5 measured |
| PRBench Legal | 49.0% | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 2 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| Design Arena: websites | 1184 | Not measured | Only GPT-5 measured |
| Design Arena: UI components | 1177 | Not measured | Only GPT-5 measured |
| Design Arena: game dev | 1185 | Not measured | Only GPT-5 measured |
| Design Arena: data viz | 1222 | Not measured | Only GPT-5 measured |
| Design Arena: 3D | 1056 | Not measured | Only GPT-5 measured |
| Design Arena: all code categories | 1167 | Not measured | Only GPT-5 measured |
| Design Arena: SVG | 1188 | Not measured | Only GPT-5 measured |
| Design Arena: ASCII art | 1141 | Not measured | Only GPT-5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index291
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5 | GPT-5.4 Nano | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
GPT-5.4 Nano costs less
Repository review
50K input + 3K output tokens
GPT-5.4 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-5.4 Nano costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5 | OpenAI GPT-5.4 Nano |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | August 7, 2025 | March 17, 2026 |
| Context window | 400K | 400K |
| Input $/Mtok | $1.25 | $0.20 |
| Output $/Mtok | $10.00 | $1.25 |
| Coding index | 38.8 | 44.8 |
| Independent measurements behind it | 3 | 2 |
| Cost per solved task | $0.39 | $0.14 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5 better than GPT-5.4 Nano for coding?
Pick GPT-5.4 Nano for coding: it scores 44.8 on the Vibe Coding Index against 38.8 for GPT-5, though on 2 benchmarks against 3. Pick GPT-5 for work measured by LiveCodeBench (Vals AI) or WeirdML, where it leads.
Which is cheaper, GPT-5 or GPT-5.4 Nano?
GPT-5 costs $1.25 per million input tokens and $10.00 per million output tokens; GPT-5.4 Nano costs $0.20 and $1.25. Per solved SWE-bench Verified task, GPT-5 costs $0.39 and GPT-5.4 Nano $0.14.
Which has the bigger context window, GPT-5 or GPT-5.4 Nano?
Neither: both take 400K tokens.
How many benchmarks is the GPT-5 vs GPT-5.4 Nano comparison based on?
76 benchmarks have a result for both models as of October 23, 2026. GPT-5's coding index rests on 3 independent benchmarks and GPT-5.4 Nano's on 2. Where only one model has a result, the page says so instead of naming a winner.