Model comparison
Amazon Nova Pro vs GPT-5.5
GPT-5.5 is the stronger model overall, scoring 63.4 to 31.0 on the Noometry Index. Amazon Nova Pro costs 8.0× less per token, which makes it the better buy when GPT-5.5's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. Amazon Nova Pro scores higher in 0 categories and GPT-5.5 in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.5 leads 81.7 to 28.5.
- Amazon Nova Pro is cheaper at $0.80 / $3.20 per million input/output tokens, against $5 / $30 for GPT-5.5.
- GPT-5.5 accepts more context: 1.05M tokens versus 300K.
Side by side
| Amazon Nova Pro | GPT-5.5 | |
|---|---|---|
| Provider | Amazon | OpenAI |
| Noometry Index | 31.0 | 63.4 |
| Released | 2024-12-03 | 2026-04-23 |
| Weights | Proprietary | Proprietary |
| Context window | 300K | 1.05M |
| Max output | 10K | 128K |
| Input $ / M tokens | $0.80 | $5 |
| Output $ / M tokens | $3.20 | $30 |
| Results tracked | 38 | 71 |
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Category by category
Coding GPT-5.5 leads
Amazon Nova Pro: 35.1 (#229), GPT-5.5: 58.2 (#17)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| LMArena Coding | 1270 | 1494 |
| SWE-bench Verified | — | 80.6% |
| DeepSWE | — | 67% |
| FrontierCode | — | 43% |
| LMArena WebDev | — | 1513 |
| SciCode | — | 56.1% |
| GSO | — | 40.2% |
| WeirdML | — | 84.9% |
| LiveBench Coding | 38.1% | — |
| MirrorCode | — | 10% |
| ALE-Bench | — | 1,943 |
Agentic & Tool Use GPT-5.5 leads
Amazon Nova Pro: 16.7 (#147), GPT-5.5: 50.7 (#6)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| Terminal-Bench | — | 84.7% |
| APEX-Agents | — | 55.1% |
| Berkeley Function Calling Leaderboard | 25% | — |
| OSWorld 2.0 | — | 13% |
| Remote Labor Index | — | 6.3% |
| TheAgentCompany | 1.7% | — |
| τ²-bench Banking | — | 44.6% |
| DeepResearch Bench | — | 54% |
| PostTrainBench | — | 27.2% |
| ExploitBench | — | 47.4% |
| GBAEval | — | 53.2% |
| GDP.pdf | — | 26% |
| LMArena Search | — | 1242 |
| Vending-Bench 2 | — | 7,524 |
Reasoning GPT-5.5 leads
Amazon Nova Pro: 20.0 (#243), GPT-5.5: 72.8 (#11)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| LMArena Hard Prompts | 1246 | 1489 |
| Epoch Capabilities Index | 123.8 | 159.1 |
| ARC-AGI-2 | — | 85% |
| SimpleBench | — | 69% |
| Kagi LLM Benchmark | — | 88.8% |
| NYT Connections (extended) | — | 96.2% |
| ARC-AGI-1 | — | 95% |
| CritPt | — | 27.1% |
| Chess Puzzles | — | 54% |
| EBR-Bench | — | 34.3% |
| LiveBench Reasoning | 32.6% | — |
| Mystery Game Puzzles | — | 56% |
| DTBench | — | 96% |
| LiveBench Data Analysis | 48.3% | — |
| LMCA | — | 54.3% |
| Surface Evolver Bench | — | 88.1% |
| Bench to the Future 3 | — | 0.14 |
| ForecastBench | — | 60.6 |
| LiveBench | 43.5% | — |
Math GPT-5.5 leads
Amazon Nova Pro: 28.5 (#243), GPT-5.5: 81.7 (#11)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| LMArena Math | 1252 | 1486 |
| FrontierMath (Tiers 1-3) | — | 85.3% |
| FrontierMath Tier 4 | — | 72.5% |
| MathArena Final-Answer Competitions | — | 94.3% |
| OTIS Mock AIME 2024-2025 | — | 100% |
| ProofBench | — | 50% |
| Omni-MATH | 24.2% | — |
| LiveBench Math | 38% | — |
| FrontierMath (Feb 2025 set) | — | 51.7% |
| FrontierMath Erdős | — | 0% |
| FrontierMath Tier 4 (v1) | — | 35.4% |
Knowledge GPT-5.5 leads
Amazon Nova Pro: 27.4 (#250), GPT-5.5: 64.4 (#17)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| Vectara Hallucination Rate | 5.1% | 9.3% |
| LMArena Expert | 1211 | 1508 |
| GPQA Diamond | — | 94% |
| Humanity's Last Exam | 4.4% | — |
| SimpleQA Verified | — | 63% |
| MMLU-Pro | 67.3% | — |
| Confabulations | 30.1% | — |
| GPQA (HELM) | 44.6% | — |
| MMLU | 82% | — |
Multimodal GPT-5.5 leads
Amazon Nova Pro: 25.0 (#126), GPT-5.5: 46.9 (#12)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| LMArena Vision | 980 | 1297 |
| Blueprint-Bench 2 | — | 36.2% |
| Furniture Assembly | — | 44.2% |
| LMArena Document | — | 1486 |
Multilingual GPT-5.5 leads
Amazon Nova Pro: 39.7 (#223), GPT-5.5: 56.4 (#20)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| LMArena Non-English | 1234 | 1467 |
| LMArena Chinese | 1244 | 1533 |
| LMArena French | 1271 | 1486 |
| LMArena German | 1243 | 1480 |
| LMArena Japanese | 1200 | 1498 |
| LMArena Korean | 1203 | 1460 |
| LMArena Russian | 1240 | 1473 |
| LMArena Spanish | 1182 | 1468 |
Instruction Following GPT-5.5 leads
Amazon Nova Pro: 64.9 (#226), GPT-5.5: 77.5 (#18)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| LMArena Instruction Following | 1235 | 1479 |
| LiveBench Instruction Following | 67.1% | — |
| IFEval | 81.5% | — |
Long Context GPT-5.5 leads
Amazon Nova Pro: 38.1 (#205), GPT-5.5: 48.3 (#12)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| LMArena Longer Query | 1255 | 1484 |
| CL-bench Life | — | 22.2% |
Writing & Preference GPT-5.5 leads
Amazon Nova Pro: 43.9 (#226), GPT-5.5: 72.7 (#13)
| Benchmark | Amazon Nova Pro | GPT-5.5 |
|---|---|---|
| LMArena Text | 1259 | 1472 |
| LMArena Creative Writing | 1212 | 1455 |
| LMArena Multi-Turn | 1246 | 1476 |
| Short-Story Creative Writing | 60.5% | — |
| EQ-Bench Creative Writing | — | 1844 |
| WildBench | 77.7% | — |
| EQ-Bench 4 | — | 1315 |
| LiveBench Language | 37% | — |
Frequently asked questions
Is Amazon Nova Pro better than GPT-5.5?
GPT-5.5 is the stronger model overall, scoring 63.4 to 31.0 on the Noometry Index. Amazon Nova Pro costs 8.0× less per token, which makes it the better buy when GPT-5.5's lead doesn't matter for your workload.
Which is cheaper, Amazon Nova Pro or GPT-5.5?
Amazon Nova Pro is cheaper. It lists at $0.80 per million input tokens and $3.20 per million output tokens; GPT-5.5 lists at $5 and $30.
Is Amazon Nova Pro or GPT-5.5 better for coding?
GPT-5.5 scores higher on coding benchmarks: 58.2 versus 35.1 in the Noometry coding category.
Which has the bigger context window?
GPT-5.5 does, with 1.05M tokens against 300K.
How many benchmarks do Amazon Nova Pro and GPT-5.5 share?
20 benchmarks have published results for both models. Amazon Nova Pro has 38 scored results on Noometry and GPT-5.5 has 71.