A high-speed, non-reasoning model from Amazon, offering strong intelligence with a premium price tag.
Nova 2.0 Omni (Non-reasoning) emerges as a compelling offering from Amazon, distinguishing itself with a remarkable blend of speed and intelligence within the non-reasoning model category. While it excels in performance metrics, its pricing strategy positions it as a premium choice, particularly for output-heavy applications. This model is designed for tasks requiring quick, accurate responses without complex inferential capabilities, making it suitable for a range of applications from content generation to data extraction where speed is paramount.
Scoring 34 on the Artificial Analysis Intelligence Index, Nova 2.0 Omni (Non-reasoning) places it comfortably above the average of 28 for comparable models. This indicates a robust capability to handle diverse prompts and generate high-quality, relevant outputs. During its intelligence evaluation, the model demonstrated a fairly concise output, generating 9.6 million tokens compared to an average of 11 million, suggesting efficiency in its responses without excessive verbosity.
However, its pricing structure warrants careful consideration. With an input token price of $0.30 per 1 million tokens and an output token price of $2.50 per 1 million tokens, Nova 2.0 Omni (Non-reasoning) is positioned at the higher end of the spectrum. The input price is somewhat above the average of $0.25, while the output price is significantly more expensive than the average of $0.60. This makes it a powerful but potentially costly solution, especially for use cases that generate substantial output.
Speed is undeniably one of Nova 2.0 Omni's strongest attributes. Achieving a median output speed of 225 tokens per second, it ranks among the fastest models benchmarked, earning a top-tier score of 93. This exceptional speed, combined with a low latency of 0.68 seconds to the first token, makes it an excellent candidate for real-time applications where rapid response is critical to user experience or system efficiency.
Beyond its core performance, Nova 2.0 Omni (Non-reasoning) offers practical versatility. It supports both text and image inputs, enabling multimodal applications, and produces text outputs. With a generous context window of 1 million tokens, it can handle extensive inputs, allowing for comprehensive document processing or long-form content generation tasks without losing context. This combination of speed, intelligence, multimodal input, and a large context window makes it a powerful tool for specific, performance-driven use cases, provided the budget aligns with its premium cost.
34 (#22 / 77 / 77)
225 tokens/s
$0.30 /M tokens
$2.50 /M tokens
9.6M tokens
0.68 seconds
| Spec | Details |
|---|---|
| Owner | Amazon |
| License | Proprietary |
| Context Window | 1M tokens |
| Input Modalities | Text, Image |
| Output Modalities | Text |
| Model Type | Non-reasoning |
| Intelligence Index Score | 34 (out of 77) |
| Output Speed (median) | 225 tokens/s |
| Latency (TTFT) | 0.68 seconds |
| Input Token Price | $0.30 / 1M tokens |
| Output Token Price | $2.50 / 1M tokens |
| Blended Price (3:1) | $0.85 / 1M tokens |
| Evaluation Cost (Intelligence Index) | $41.85 |
| Intelligence Index Verbosity | 9.6M tokens |
Choosing the right model often involves balancing performance with cost. Nova 2.0 Omni (Non-reasoning) excels in specific areas, making it a prime candidate for certain priorities, while its cost structure suggests caution for others.
| Priority | Pick | Why | Tradeoff to accept |
|---|---|---|---|
| Priority | Pick | Why | Tradeoff |
| Maximum Speed | Nova 2.0 Omni | Top-tier output speed (225 tokens/s) and low latency. | Significantly higher output token costs. |
| Non-Reasoning Intelligence | Nova 2.0 Omni | Above-average Intelligence Index score (34) for its class. | Premium pricing compared to other non-reasoning models. |
| Multimodal Input (Text & Image) | Nova 2.0 Omni | Seamlessly handles both text and image inputs. | Higher overall cost for multimodal processing. |
| Large Context Processing | Nova 2.0 Omni | 1M token context window supports extensive inputs. | Cost implications for very long input prompts. |
| Cost-Efficiency (Output-Heavy) | Consider Alternatives | Nova 2.0 Omni's output price is very high, making it uneconomical for high-volume generation. | May sacrifice some speed or intelligence. |
These recommendations are based on benchmarked performance and pricing. Actual optimal choice may vary based on specific application requirements and budget constraints.
Understanding the real-world cost implications of Nova 2.0 Omni (Non-reasoning) requires looking at typical use cases. The following scenarios illustrate estimated costs based on its input and output token prices.
| Scenario | Input | Output | What it represents | Estimated cost |
|---|---|---|---|---|
| Scenario | Input | Output | What it represents | Estimated cost |
| Image Captioning | 1 image + 50 tokens | 100 tokens | Generating descriptive text for an image. | $0.000265 |
| Data Extraction | 500 tokens | 50 tokens | Extracting structured information from a short document. | $0.000275 |
| Content Summarization | 1,000 tokens | 200 tokens | Condensing a medium-length article into a summary. | $0.000800 |
| Chatbot Response | 100 tokens | 75 tokens | A single turn in an interactive customer support chat. | $0.000218 |
| Document Analysis | 5,000 tokens | 150 tokens | Quick insights or classification from a longer document. | $0.001875 |
These examples highlight that while input costs are manageable, the high output token price significantly drives up the total cost, especially for tasks requiring more extensive generation. Users should carefully estimate their expected output volume.
To leverage Nova 2.0 Omni (Non-reasoning) effectively while managing costs, consider these strategies:
Given the high output token price, minimizing the length of generated responses is crucial. Design prompts to encourage concise answers and implement post-processing to trim unnecessary verbosity.
For tasks involving multiple independent prompts, consider batching them into a single API call if supported. This can reduce overhead and potentially improve throughput, though the per-token cost remains the same.
While the input price is lower than output, it's still above average. Ensure your input prompts are as lean as possible, providing only necessary context without redundancy.
Proactively track your token consumption, especially output tokens. Set up alerts and budget limits with your provider to prevent unexpected cost overruns.
If your application primarily involves generating large volumes of text, Nova 2.0 Omni (Non-reasoning) might not be the most cost-effective choice. Consider using it for critical, high-value tasks and cheaper models for high-volume, less critical generation.
Nova 2.0 Omni (Non-reasoning) is a high-performance AI model from Amazon designed for tasks that require fast and intelligent text generation or analysis without complex reasoning capabilities. It supports both text and image inputs.
It scores 34 on the Artificial Analysis Intelligence Index, placing it above the average for non-reasoning models. This indicates strong performance in understanding and generating relevant content.
Yes, with a median output speed of 225 tokens per second and a low latency of 0.68 seconds to first token, it is exceptionally well-suited for real-time applications requiring rapid responses.
The primary cost driver is its high output token price ($2.50 per 1M tokens), which is significantly above average. Input token price is also somewhat higher than average.
Yes, Nova 2.0 Omni (Non-reasoning) is a multimodal model that supports both text and image inputs, allowing for applications like image captioning or visual content analysis.
It features a large context window of 1 million tokens, enabling it to process and generate responses based on very extensive input documents or conversations.
Nova 2.0 Omni is owned by Amazon and is offered under a proprietary license.