GPT-5 nano vs Amazon Nova Pro
Benchmarks, API pricing and specs, head to head. Data updated 2026-06-10.
GPT-5 nano
OpenAI · Aug 2025
OpenAI's cheapest model — $0.05 per million input tokens — for latency-critical routing, autocomplete and bulk tagging.
Amazon Nova Pro
Amazon · Dec 2024
AWS's house multimodal model — chosen for Bedrock-native integration and AWS billing more than for benchmark wins.
The verdict
These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: GPT-5 nano works out roughly 10x cheaper per blended million tokens. GPT-5 nano also takes 400K of context versus 300K for Amazon Nova Pro.
Specs & pricing
| GPT-5 nano | Amazon Nova Pro | |
|---|---|---|
| modhub Index | — | — |
| Input price / 1M | $0.05 | $0.8 |
| Output price / 1M | $0.4 | $3.2 |
| Context window | 400K | 300K |
| Max output | 128K | 10K |
| Open weights | no | no |
| Reasoning model | yes | no |
| Multimodal input | text, image | text, image, video |
| Knowledge cutoff | May 2024 | Oct 2024 |
| Released | Aug 2025 | Dec 2024 |
| Example monthly cost* | $1.10 | $12.80 |
* 10M input + 1.5M output tokens per month at list prices, no caching. Green = better value on that row.
Frequently asked questions
- Which is better, GPT-5 nano or Amazon Nova Pro?
- These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: GPT-5 nano works out roughly 10x cheaper per blended million tokens. GPT-5 nano also takes 400K of context versus 300K for Amazon Nova Pro.
- Which is cheaper, GPT-5 nano or Amazon Nova Pro?
- GPT-5 nano costs $0.05/$0.4 per million input/output tokens, while Amazon Nova Pro costs $0.8/$3.2. For a typical workload of 10M input and 1.5M output tokens per month, that's $1.10 versus $12.80.
- Which model is better for coding, GPT-5 nano or Amazon Nova Pro?
- We don't yet track SWE-bench Verified results for both models; check their individual pages for coding-related scores.