Nova Pro 1.0 vs GPT-5.1-Codex
GPT-5.1-Codex leads Nova Pro 1.0 on the Artificial Analysis Intelligence Index, 23.7 to 7.0, and Nova Pro 1.0 costs 3.1x less per output token ($3.20 vs $10.00 per million). Updated October 21, 2026; 12 benchmarks have a result for both.
Nova Pro 1.0 or GPT-5.1-Codex: which to pick
Only GPT-5.1-Codex has a coding score, 15.3 on the Vibe Coding Index; Nova Pro 1.0 has none, so the two cannot be ranked on coding.
Pick Nova Pro 1.0 for output tokens 3.1x cheaper ($3.20 vs $10.00 per million).
- Shared results
- 12
- Nova Pro 1.0 only
- 30
- GPT-5.1-Codex only
- 14
- Like-for-like categories
- 8 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
No call
Only GPT-5.1-Codex has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.1-Codex
GPT-5.1-Codex leads, 23.7 against 7.0.
Same board, both measured
Web design
Design Arena: websites
GPT-5.1-Codex
GPT-5.1-Codex leads, 1162 against 796.
Same board, both measured
Long documents
Listed context window
GPT-5.1-Codex
GPT-5.1-Codex takes 400K tokens against 300K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nova Pro 1.0
Nova Pro 1.0 $0.0024, GPT-5.1-Codex $0.0063 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.1-Codex has the number, $0.892.
Directional only
At a glance
- Coding index
- Nova Pro 1.0 not benchmarked, GPT-5.1-Codex 15.3 from 2 benchmarks.
- Widest category
- Math, 88.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Math Index: Nova Pro 1.0 7.0 against GPT-5.1-Codex 95.7, 88.7 points apart on a 0 to 100 scale.
- Output price
- Nova Pro 1.0 $3.20 against GPT-5.1-Codex $10.00 per million output tokens, 3.1x apart.
- Context window
- Nova Pro 1.0 takes 300K tokens, GPT-5.1-Codex 400K.
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 | Nova Pro 1.0 | Bars | GPT-5.1-Codex | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| Web design | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 12 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Nova Pro 1.0 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 66.0% | Only GPT-5.1-Codex measured |
| LMArena WebDev | Not measured | 1337 | Only GPT-5.1-Codex measured |
| LiveCodeBench (Vals AI) | Not measured | 85.5% | Only GPT-5.1-Codex measured |
| Vibe Code Bench (Vals AI) | Not measured | 13.1% | Only GPT-5.1-Codex measured |
| LiveCodeBench (Artificial Analysis run) | 23.3% | 84.9% | GPT-5.1-Codex |
| Terminal-Bench Hard (Artificial Analysis run) | 6.1% | 34.8% | GPT-5.1-Codex |
| Terminal-Bench | Not measured | 57.8% | Only GPT-5.1-Codex measured |
| ALE-Bench | Not measured | 1244.9 | Only GPT-5.1-Codex measured |
| LMArena Text: coding | 1270 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: software and IT | 1271 | Not measured | Only Nova Pro 1.0 measured |
| LMArena WebDev: HTML | Not measured | 1346 | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.0 | 23.7 | GPT-5.1-Codex |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1018 | Only GPT-5.1-Codex measured |
| Design Arena: agents building full-stack apps | Not measured | 1086 | Only GPT-5.1-Codex measured |
| Design Arena: agents building mobile apps | Not measured | 1191 | Only GPT-5.1-Codex measured |
| τ²-Bench Telecom | 14.0% | 83.0% | GPT-5.1-Codex |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Pro 1.0 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 49.9% | 86.0% | GPT-5.1-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 3.2% | 25.7% | GPT-5.1-Codex |
| LMArena Text: hard prompts | 1246 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: expert | 1211 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: hard prompts in English | 1259 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 17 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Pro 1.0 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| AA Math Index | 7.0 | 95.7 | GPT-5.1-Codex |
| AIME 2025 (Artificial Analysis run) | 7.0% | 95.7% | GPT-5.1-Codex |
| LMArena Text: math | 1252 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: mathematical work | 1261 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 69.1% | 86.0% | GPT-5.1-Codex |
| MMLU | 82.0% | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: science | 1255 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: medicine and healthcare | 1260 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: legal and government | 1281 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: business and finance | 1229 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Nova Pro 1.0 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| Design Arena: websites | 796 | 1162 | GPT-5.1-Codex |
| Design Arena: UI components | Not measured | 1237 | Only GPT-5.1-Codex measured |
| Design Arena: game dev | Not measured | 1138 | Only GPT-5.1-Codex measured |
| Design Arena: data viz | Not measured | 1213 | Only GPT-5.1-Codex measured |
| Design Arena: all code categories | Not measured | 1152 | Only GPT-5.1-Codex measured |
| Neither model has a result on the other 4 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Nova Pro 1.0 | GPT-5.1-Codex | Leader |
|---|---|---|---|
| IFBench | 38.1% | 70.0% | GPT-5.1-Codex |
| Long context reasoning (AA-LCR) | 21.0% | 69.3% | GPT-5.1-Codex |
| LMArena Text | 1259 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: instruction following | 1235 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: creative writing | 1212 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Vision | 980 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: English | 1276 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: non-English | 1233 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Chinese | 1244 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: German | 1243 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Japanese | 1200 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Korean | 1203 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: French | 1271 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Spanish | 1182 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: Russian | 1240 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: multi-turn | 1246 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: longer queries | 1255 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: writing and language | 1247 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Text: entertainment and media | 1210 | Not measured | Only Nova Pro 1.0 measured |
| LMArena Vision: English | 987 | Not measured | Only Nova Pro 1.0 measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Nova Pro 1.0 | GPT-5.1-Codex | 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
Nova Pro 1.0 costs less
Repository review
50K input + 3K output tokens
Nova Pro 1.0 costs less
Agent loop
200K input + 10K output tokens
Nova Pro 1.0 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 | Amazon Nova Pro 1.0 | OpenAI GPT-5.1-Codex |
|---|---|---|
| Maker | Amazon | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | December 5, 2024 | November 13, 2025 |
| Context window | 300K | 400K |
| Input $/Mtok | $0.80 | $1.25 |
| Output $/Mtok | $3.20 | $10.00 |
| Coding index | Not benchmarked | 15.3 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $0.892 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Nova Pro 1.0 better than GPT-5.1-Codex for coding?
Only GPT-5.1-Codex has a coding score, 15.3 on the Vibe Coding Index; Nova Pro 1.0 has none, so the two cannot be ranked on coding. Pick Nova Pro 1.0 for output tokens 3.1x cheaper ($3.20 vs $10.00 per million).
Which is cheaper, Nova Pro 1.0 or GPT-5.1-Codex?
Nova Pro 1.0 costs $0.80 per million input tokens and $3.20 per million output tokens; GPT-5.1-Codex costs $1.25 and $10.00. Cost per solved task is known for GPT-5.1-Codex only.
Which has the bigger context window, Nova Pro 1.0 or GPT-5.1-Codex?
GPT-5.1-Codex, with 400K tokens against 300K.
How many benchmarks is the Nova Pro 1.0 vs GPT-5.1-Codex comparison based on?
12 benchmarks have a result for both models as of October 21, 2026. Nova Pro 1.0's coding index rests on 0 independent benchmarks and GPT-5.1-Codex's on 2. Where only one model has a result, the page says so instead of naming a winner.