Nova 2.0 Pro Preview (Non-reasoning)
Amazon • text#411 of 704 in intelligence
Data source: Artificial Analysis · ID AA: a20ae33a-46e1-41e6-81a0-fe8b00d2e538 · Snapshot published: 10/27/2026, 3:00:24 PM · Methodology version: 4.3
Specifications
AA Intelligence Index
10.0
Artificial Analysis · 4.3 · 10/27/2026, 3:00:24 PM
Context Window
—
Input Price/1M
$1.25
#275 of 445
Output Price/1M
$10.00
Parameters
—
Speed
119 tok/s
#66 of 160
Latency (TTFT)
1.1s
Cost per Task
—
USD / task · lower is better · Artificial Analysis · 4.3 · 10/27/2026, 3:00:24 PM
Benchmarks
Artificial Analysis metrics for Nova 2.0 Pro Preview (Non-reasoning). Higher is better for capability indexes; lower is better for cost per task.
Coding
| Benchmark | Score | Maximum | Methodology | Source / version / date |
|---|---|---|---|---|
| AA Coding Index | 20.9 | 100.0 | Artificial Analysis official API | Artificial Analysis · 4.3 · 10/27/2026 |
overall
| Benchmark | Score | Maximum | Methodology | Source / version / date |
|---|---|---|---|---|
| AA Intelligence Index | 10.0 | 100.0 | Artificial Analysis official API | Artificial Analysis · 4.3 · 10/27/2026 |
Information
- Release date
- November 27, 2025
- Tool Calling
- ❌ Not supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: Nova 2.0 Pro Preview (Non-reasoning)
What is Nova 2.0 Pro Preview (Non-reasoning)?
Nova 2.0 Pro Preview (Non-reasoning) is an AI model developed by Amazon, classified as a text model. It focuses on text processing and natural language generation. As a proprietary model, it is available via Amazon's cloud API.
Pricing & Costs in 2026
Nova 2.0 Pro Preview (Non-reasoning) is usage-based, priced at $1.25/1M input tokens and $10/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. The mid-range pricing balances quality and cost for most professional applications.
Benchmarks & Performance
Nova 2.0 Pro Preview (Non-reasoning) was evaluated on 2 different benchmarks, covering categories like Coding, overall. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
Nova 2.0 Pro Preview (Non-reasoning) specializes in text, offering advanced capabilities for creating and processing text content.
Comparison with Alternatives
In the 2026 AI model ecosystem, Nova 2.0 Pro Preview (Non-reasoning) competes directly with similarly capable models. Amazon competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is Nova 2.0 Pro Preview (Non-reasoning)?
Nova 2.0 Pro Preview (Non-reasoning) is an AI model developed by Amazon. It is a text model.
How much does Nova 2.0 Pro Preview (Non-reasoning) cost?
Nova 2.0 Pro Preview (Non-reasoning) costs $1.25/1M input tokens and $10/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does Nova 2.0 Pro Preview (Non-reasoning) compare with other models?
In available benchmarks, Nova 2.0 Pro Preview (Non-reasoning) scored: AA Coding Index: 20.9/100, AA Intelligence Index: 10/100. See the full table above for a detailed comparison.
Is Nova 2.0 Pro Preview (Non-reasoning) open source?
No, Nova 2.0 Pro Preview (Non-reasoning) is a proprietary model from Amazon. It is available via cloud API. For open source alternatives, check our open source model ranking.
What is Nova 2.0 Pro Preview (Non-reasoning) best for?
Nova 2.0 Pro Preview (Non-reasoning) excels at general-purpose language tasks.
Last updated: October 27, 2026 • View methodology →