Nova Lite (non-reasoning)

Amazon's Fast, Concise, and Image-Capable Model

Nova Lite (non-reasoning)

Nova Lite is a high-speed, image-input capable model from Amazon, offering above-average intelligence and conciseness, though positioned at a premium price point.

Image Input300k ContextHigh SpeedAbove Average IntelligenceConcise OutputProprietary

Nova Lite, developed by Amazon, emerges as a compelling option in the landscape of non-reasoning AI models, particularly for applications demanding rapid processing and multimodal capabilities. Benchmarked extensively on Amazon Bedrock, this model distinguishes itself with an impressive median output speed of 157 tokens per second, significantly outpacing the average model performance. Its low latency of 0.40 seconds to first token further solidifies its position as a strong contender for real-time or near real-time interactive applications where responsiveness is paramount.

Beyond raw speed, Nova Lite demonstrates an above-average intelligence, scoring 21 on the Artificial Analysis Intelligence Index, which places it comfortably above the average of 15 for comparable models. This intelligence is delivered with remarkable conciseness; during its Intelligence Index evaluation, Nova Lite generated 5.3 million tokens, considerably less verbose than the average of 8.1 million tokens. This combination of speed, intelligence, and conciseness makes it well-suited for tasks requiring efficient summarization, content generation, or rapid information extraction without excessive verbosity.

However, Nova Lite's premium performance comes with a corresponding price tag. With an input token price of $0.06 per 1 million tokens and an output token price of $0.24 per 1 million tokens, it is positioned at the higher end of the spectrum, especially when compared to models that might offer similar capabilities at a lower cost. The blended price, calculated at $0.10 per 1 million tokens (based on a 3:1 input-to-output ratio), reflects this premium. While its pricing is notably higher than the reported average of $0.00 for both input and output tokens (which often signifies models with extremely low costs or free tiers), its performance metrics, particularly in speed and intelligence, may justify the investment for specific use cases.

A significant feature of Nova Lite is its support for image input, expanding its utility into multimodal applications such as image captioning, visual question answering, or document analysis. Coupled with a substantial 300,000-token context window, it can process and understand extensive textual and visual information, making it adaptable for complex, long-form content analysis or interactive sessions. This blend of multimodal input, expansive context, and high-speed, intelligent output positions Nova Lite as a powerful, albeit premium, tool for developers leveraging the Amazon Bedrock ecosystem.

Scoreboard

Intelligence

21 (#28 / 93 / 93)

Scores 21 on the Artificial Analysis Intelligence Index, placing it above average among comparable models (average: 15).
Output speed

157 tokens/s

Achieves a median output speed of 157 tokens per second, significantly faster than the average of 77 tokens/s.
Input price

$0.06 per 1M tokens

Input tokens are priced at $0.06 per 1M, which is on the higher end compared to many models.
Output price

$0.24 per 1M tokens

Output tokens are priced at $0.24 per 1M, also a premium rate in the current market.
Verbosity signal

5.3M tokens

Generated 5.3M tokens during Intelligence Index evaluation, indicating good conciseness compared to the average of 8.1M.
Provider latency

0.40 seconds

Exhibits a low latency of 0.40 seconds to first token, crucial for responsive applications.

Technical specifications

Spec Details
Owner Amazon
License Proprietary
Context Window 300,000 tokens
Image Input Supported
Intelligence Index Score 21 (Rank #28/93)
Output Speed (Median) 157 tokens/s (Rank #10/93)
Latency (TTFT) 0.40 seconds
Input Token Price $0.06 per 1M tokens (Rank #83/93)
Output Token Price $0.24 per 1M tokens (Rank #86/93)
Blended Price (3:1) $0.10 per 1M tokens
Verbosity (Intelligence Index) 5.3M tokens (Rank #12/93)
Model Type Non-reasoning

What stands out beyond the scoreboard

Where this model wins
  • High-Speed Output: With 157 tokens/s, Nova Lite is among the fastest models, ideal for applications requiring rapid content generation or summarization.
  • Low Latency: A 0.40-second Time To First Token (TTFT) ensures highly responsive user experiences, critical for interactive chatbots or real-time assistants.
  • Above-Average Intelligence: Scores 21 on the Intelligence Index, indicating strong performance in understanding and generating relevant content, surpassing many peers.
  • Concise Outputs: Its lower verbosity (5.3M tokens vs. 8.1M average) means less token consumption for equivalent information, potentially offsetting some of its higher per-token cost.
  • Multimodal Capabilities: Support for image input opens doors for advanced applications like visual content analysis, image captioning, and document processing.
  • Large Context Window: A 300k token context window allows for processing and understanding extensive documents or maintaining long, complex conversations.
Where costs sneak up
  • Premium Per-Token Pricing: Both input ($0.06/1M) and output ($0.24/1M) token prices are significantly higher than many alternatives, making high-volume usage expensive.
  • Blended Price Impact: The $0.10/1M blended price, while seemingly moderate, can quickly accumulate for applications with imbalanced input/output ratios or extensive generation.
  • Long Context Window Misuse: While powerful, consistently filling the 300k context window with unnecessary information will lead to substantially higher input costs.
  • Image Input Overhead: Processing images, especially high-resolution ones, can incur additional computational costs that might not be directly reflected in token pricing but impact overall operational expenses.
  • Lack of Tiered Pricing: Without clear volume discounts or tiered pricing, costs remain high even for large-scale deployments, unlike some competitors.
  • Vendor Lock-in: Being an Amazon proprietary model, switching providers later could involve significant re-engineering efforts and costs.

Provider pick

Choosing the right model often comes down to balancing performance, features, and cost against specific application requirements. For Nova Lite, its strengths lie in speed, intelligence, and multimodal capabilities, making it a strong contender within the Amazon Bedrock ecosystem. However, its premium pricing necessitates careful consideration of usage patterns and budget constraints.

Given that Nova Lite is an Amazon proprietary model, the primary provider is Amazon Bedrock. The following recommendations assume you are operating within or considering the Amazon Bedrock environment, focusing on how to best leverage Nova Lite for different priorities.

Priority Pick Why Tradeoff to accept
Priority Pick Why Tradeoff
Maximum Responsiveness Nova Lite (Amazon Bedrock) Exceptional 0.40s TTFT and 157 tokens/s output speed ensure a fluid, real-time user experience. Higher per-token cost for both input and output.
Multimodal Content Generation Nova Lite (Amazon Bedrock) Supports image input alongside a large text context, ideal for visual content analysis and generation. Cost can escalate quickly with complex multimodal prompts and extensive outputs.
Concise & Intelligent Summarization Nova Lite (Amazon Bedrock) Above-average intelligence (21) combined with low verbosity (5.3M tokens) delivers efficient, high-quality summaries. More expensive than models that might offer similar summarization quality at a lower cost per token.
High Throughput Applications Nova Lite (Amazon Bedrock) Its top-tier output speed makes it suitable for processing large volumes of requests quickly. The cumulative cost for high-volume processing will be substantial due to premium pricing.
Long-Context Document Analysis Nova Lite (Amazon Bedrock) 300k context window is excellent for analyzing lengthy documents or complex datasets. Filling the large context window frequently will significantly increase input token costs.

Note: These recommendations are based on Nova Lite's benchmarked performance within the Amazon Bedrock ecosystem. Alternative models from other providers might offer different cost-performance profiles.

Real workloads cost table

Understanding the real-world cost implications of Nova Lite requires looking beyond per-token prices and considering typical usage scenarios. Below are estimated costs for common AI workloads, assuming usage on Amazon Bedrock. These estimates highlight how Nova Lite's speed and intelligence can be leveraged, while also pointing out where its premium pricing becomes most apparent.

For these calculations, we assume a 3:1 input-to-output token ratio for blended pricing where applicable, and use Nova Lite's benchmarked speeds and prices. Actual costs may vary based on specific prompt engineering, output length, and API call patterns.

Scenario Input Output What it represents Estimated cost
Scenario Input Output What it represents Estimated cost
Short Chatbot Interaction 500 tokens 150 tokens A single turn of a concise, interactive customer support chatbot. $0.000039
Article Summarization 10,000 tokens 1,000 tokens Summarizing a medium-length article into a brief overview. $0.00084
Long Document Q&A 200,000 tokens 500 tokens Extracting specific answers from a large legal document or research paper. $0.01212
Image Captioning (Complex) Image + 100 tokens text 200 tokens Generating a detailed description for a complex image based on a short prompt. $0.000054
Content Generation (Marketing) 2,000 tokens 5,000 tokens Drafting a marketing email or social media post from bullet points. $0.00132
Daily Report Generation 50,000 tokens 10,000 tokens Automated daily summary of business metrics or news feeds. $0.0054
High-Volume API Calls (1M tokens/day) 750,000 tokens 250,000 tokens Continuous stream of short requests, e.g., real-time data processing. $0.10 per day

Nova Lite's costs are manageable for individual, short interactions, but scale rapidly with increased token usage, especially for output-heavy or long-context tasks. Its premium pricing means that while performance is excellent, cost optimization strategies are crucial for high-volume or extensive deployments.

How to control cost (a practical playbook)

Optimizing costs with Nova Lite, given its premium pricing, requires a strategic approach. While its performance is top-tier, careful management of token usage, prompt engineering, and output generation can significantly impact your operational expenses. The following playbook outlines key strategies to maximize value while keeping costs in check.

These tactics are particularly relevant for applications deployed on Amazon Bedrock, where Nova Lite's capabilities are leveraged. Implementing these practices can help ensure that you benefit from Nova Lite's speed and intelligence without incurring unnecessary expenditures.

Optimize Prompt Length & Density

Given Nova Lite's $0.06/1M input token price, every token in your prompt counts. Focus on providing only essential information.

  • Be Concise: Remove redundant words, filler phrases, and unnecessary examples from your prompts.
  • Leverage Context Effectively: Utilize the 300k context window for critical information, but avoid stuffing it with irrelevant data. Summarize historical conversations or documents before feeding them to the model if possible.
  • Instruction Compression: Experiment with shorter, clearer instructions. Often, a well-phrased short instruction is more effective than a verbose one.
Manage Output Verbosity

At $0.24/1M output tokens, controlling the length of Nova Lite's responses is paramount. While Nova Lite is naturally concise, explicit instructions can further refine output.

  • Specify Length Constraints: Use prompt instructions like "Summarize in 3 sentences," "Provide 5 bullet points," or "Keep response under 100 words."
  • Iterative Generation: For complex tasks, consider breaking down the output into smaller, controlled chunks rather than generating one massive response.
  • Post-Processing: Implement a post-processing step to trim or filter unnecessary parts of the model's output before it reaches the end-user.
Strategic Use of Image Input

Nova Lite's image input capability is powerful but can be resource-intensive. Use it judiciously to avoid hidden costs.

  • Resolution & Compression: Optimize image resolution and compression before sending them to the model. Higher quality images consume more resources.
  • Conditional Image Use: Only send images when absolutely necessary for the task. For purely text-based queries, avoid including visual data.
  • Batch Processing: If possible, batch image-related tasks to potentially benefit from more efficient resource allocation on the backend.
Monitor & Analyze Usage Patterns

Continuous monitoring of your token consumption is vital for identifying cost-saving opportunities.

  • Track Token Counts: Implement logging to track input and output token counts for different types of requests.
  • Identify High-Cost Workflows: Pinpoint which applications or user interactions are generating the most tokens and focus optimization efforts there.
  • Set Budget Alerts: Utilize Amazon Bedrock's cost management tools to set alerts for when your spending approaches predefined thresholds.

FAQ

What is Nova Lite's primary strength?

Nova Lite's primary strengths lie in its exceptional speed (157 tokens/s output, 0.40s latency) and its ability to handle multimodal inputs, particularly images, alongside a large 300k token context window. It also offers above-average intelligence with concise outputs.

Is Nova Lite suitable for cost-sensitive applications?

While Nova Lite offers premium performance, its pricing ($0.06/1M input, $0.24/1M output) is on the higher side. For extremely cost-sensitive applications with high volume, it might be more expensive than alternatives. However, its conciseness can help mitigate some costs by reducing output token usage.

How does Nova Lite's intelligence compare to other models?

Nova Lite scores 21 on the Artificial Analysis Intelligence Index, which is above the average of 15 for comparable models. This indicates a strong capability in understanding and generating relevant, high-quality content, positioning it as an intelligent choice for many tasks.

What kind of applications benefit most from Nova Lite's features?

Applications requiring real-time interaction (chatbots, virtual assistants), high-throughput content generation, multimodal analysis (e.g., image captioning, visual Q&A), and processing of very long documents (due to its 300k context window) will benefit significantly from Nova Lite.

Can Nova Lite process images?

Yes, Nova Lite supports image input, making it a multimodal model. This allows it to understand and respond to queries that involve both textual and visual information, expanding its utility for diverse use cases.

What is the significance of its 300k context window?

A 300,000-token context window means Nova Lite can process and retain a vast amount of information within a single interaction or document. This is particularly useful for tasks like summarizing entire books, analyzing extensive legal contracts, or maintaining very long, complex conversations without losing context.

How does Nova Lite's conciseness impact its cost-effectiveness?

Despite its higher per-token price, Nova Lite's conciseness (generating 5.3M tokens during evaluation compared to an 8.1M average) means it often provides necessary information with fewer output tokens. This can partially offset its premium pricing, making it more cost-effective for tasks where brevity is desired and valued.


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