Intelligence
18
score
Nova 2.0 Lite (low) scores 18 (estimated) on the Artificial Analysis Intelligence Index, placing it …
vs class avg: 15
Amazon•Open weights•October 29, 2025
Nova 2.0 Lite (low)
Intelligence, Performance & Price Analysis
Source:Artificial Analysis scrapeType:Open weights
Speed
142.3
output tokens/sec
Nova 2.0 Lite (low) generates output at 142.3 tokens per second (based on Amazon's API), which is …
Latency
13.03s
TTFT
Nova 2.0 Lite (low) has a time to first token (TTFT) of 13.03s (based on Amazon's API), which is at …
Input Price#98/161
$0.30
/ 1M tokens
Nova 2.0 Lite (low) costs $0.30 per 1M input tokens (somewhat higher than average, median: $0. …
Output Price#150/161
$2.50
/ 1M tokens
Nova 2.0 Lite (low) costs $0.30 per 1M input tokens (somewhat higher than average, median: $0. …
Decision Overview
Ethen's intelligence-driven routing assessment for this model
Overall verdict
Capable everyday model
Good for routine tasks; route complex reasoning and premium workloads to stronger models.
Best for
- Routine Q&A
- Content summarization
- Classification
- Light coding
- Low-latency chat
Weak or unsuitable
- Complex reasoning
- Agentic workflows
- Research-grade analysis
- Predictable high-volume throughput
Routing recommendation
1
Cheaper routes for predictable extraction, labeling, or summarization
2
Cache-backed reuse for repeated prompts
Cost pressure
Moderate pricing — $0.30 / M input, $2.50 / M output. Costs are manageable, but volume should still be reviewed.
Model-fit matrix
Use this model where capability pays for itself; route away where volume, latency, or budget dominate.
| Use case | Fit | Reason | Routing note |
|---|---|---|---|
| Complex reasoning & agentic workflows | Moderate | Intelligence score 18 handles routine reasoning but may struggle with open-ended agentic tasks. | Route simpler sub-tasks here; keep hard reasoning on a stronger model. |
| High-volume chat & customer-facing | Excellent | Output speed 142.3 tokens/sec and capable intelligence make this suitable for real-time chat at scale. | Ideal for interactive chat; enable caching for repeated queries. |
| Latency-sensitive applications | Moderate | TTFT 13.03s — latency may be noticeable in interactive use. | Consider routing latency-critical paths to faster models. |
| Cost-sensitive pipelines | Moderate | Output pricing at $2.50 is premium. Route high-volume simple tasks to cheaper alternatives. | Use only for high-value tasks; route simple queries to budget models. |
Cost pressure
MediumPricing is moderate — input $0.30, output $2.50. Costs accumulate at volume but are manageable for valuable tasks.
Cheaper substitutes
- Cheaper routes for predictable extraction, labeling, or summarization
Route away when
- Predictable high-volume throughput
- Non-critical classification and extraction
Highlights
Key benchmark results at a glance.
Intelligence
Intelligence position
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Nova 2.0 Lite (low) scores 18 (estimated) on the Artificial Analysis Intelligence Index, placing it above average among other reasoning models in a similar price tier (median: 15).
Speed
Speed position
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Nova 2.0 Lite (low) generates output at 142.3 tokens per second (based on Amazon's API), which is above average compared to other reasoning models in a similar price tier (median: 99.0 t/s).
Context, Cost & Pricing
Price/value position
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Pricing is moderate — input $0.30, output $2.50. Costs accumulate at volume but are manageable for valuable tasks.
Intelligence & Quality
Benchmark scores and quality indices measuring model capability.
AA-Omniscience Index
AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Artificial Analysis Intelligence Index by Open Weights / Proprietary
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Intelligence
Artificial Analysis Intelligence Index · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Speed & Throughput
Output tokens per second and generation throughput.
Output Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Speed should be read together with latency and cost; fast output does not always mean better user-perceived performance.
Speed
Output tokens per second · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Speed should be read together with latency and cost; fast output does not always mean better user-perceived performance.
Latency & Response Time
Time to first token and end-to-end response latency.
End-to-End Response Time
Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Latency: Time To First Answer Token
Seconds to first answer token received · Accounts for reasoning model 'thinking' time · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Latency includes thinking / reasoning time when applicable. Lower is better for interactive use cases.
Context, Cost & Pricing
Context window size, cost per task, and token pricing.
Context Window
Context window: tokens limit · Higher is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Larger context windows enable complex multi-turn tasks but may increase latency and cost for long inputs.
Cost per Intelligence Index Task
Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Cost per Task
Weighted average cost (USD) per Intelligence Index task · Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Ethen Gateway should route away from this model when the task is simple, repetitive, or likely to generate many output tokens.
Pricing: Cache Hit, Input, and Output
Price (USD per M Tokens) · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Bars intentionally show many models at once so the page feels like a benchmark report rather than a dashboard.
Time per Intelligence Index Task
Weighted average decode time (minutes) per task; excludes TTFT and overhead time · Lower is better · Evaluation results measured independently by Artificial Analysis
Source and methodology are summarized below
Chart source and provenance are listed in Methodology & sources below.
Higher values indicate stronger overall capability. Bars show how models compare on composite intelligence metrics.
Specifications
Technical Specifications
Nova 2.0 Lite (low) scores 18 (estimated) on the Artificial Analysis Intelligence Index, placing it above average among other reasoning models in a similar price tier (median: 15). Nova 2.0 Lite (low) generates output at 142.3 tokens per second (based on Amazon's API), which is above average compared to other reasoning models in a similar price tier (median: 99.0 t/s). Nova 2.0 Lite (low) costs $0.30 per 1M input tokens (somewhat higher than average, median: $0.25) and $2.50 per 1M output tokens (at the higher end, median: $0.87), based on Amazon's API.
Nova 2.0 Lite (low)
- Model type
- Open weights
- Reasoning
- Yes
- Input modalities
- Nova 2.0 Lite (low) supports text and image input.
- Output modalities
- Nova 2.0 Lite (low) supports text output.
- Context window
- Nova 2.0 Lite (low) has a context window of 1.0M tokens. This determines how much text and conversation history the model can process in a single request.
- Open weights / source
- No, Nova 2.0 Lite (low) is proprietary. The model weights are not publicly available.
- Parameters
- Nova 2.0 Lite (low) is a proprietary model and Amazon has not disclosed the model size or parameter count.
- API availability
- Yes, Nova 2.0 Lite (low) is available via API through 1 provider.
Methodology & Provenance
This page is rendered from the normalized profile and page JSON for Nova 2.0 Lite (low).
Benchmark values are preserved as normalized; only layout, disclosure ordering, and typography are adjusted for readability.
Source file: md/scrape/artificial_analysis_model_pages/artificialanalysis_ai__models__nova-2-0-lite-reasoning-low__33e895f095.html · Canonical URL: https://artificialanalysis.ai/models/nova-2-0-lite-reasoning-low
Normalized at: 2026-07-08T03:24:56+00:00 Technical specs, comparison summary, and FAQs are passed through from the normalized data without rewriting.
Ranks shown on summary cards come directly from the normalized profile. No rank or class display is synthesized in the renderer.
Visible FAQ answers and FAQ JSON-LD are emitted from the same normalized FAQ array, so structured data stays aligned with the rendered accordion.
Time per Intelligence Index Task: https://artificialanalysis.ai/models/nova-2-0-lite-reasoning-low
Frequently Asked Questions
Nova 2.0 Lite (low) was released on October 29, 2025.
Nova 2.0 Lite (low) was created by Amazon.
Nova 2.0 Lite (low) scores 18 (estimated) on the Artificial Analysis Intelligence Index, placing it above average among other reasoning models in a similar price tier (median: 15).