Amazon: Nova 2 Lite
Nova 2 Lite is a fast, cost-effective reasoning model for everyday workloads that can process text, images, and videos to generate text. Nova 2 Lite demonstrates standout capabilities in processing...
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Verdict
Best for
- High-volume document classification at scale
- Cost-sensitive multimodal content moderation
- Batch summarization of mixed text and images
- Prototyping before upgrading to frontier models
- Long-context file analysis on tight budgets
Strengths
The million-token context window lets you drop entire codebases, multi-hour video transcripts, or hundreds of pages of PDFs into a single call without chunking. Multimodal support across text, images, video, and files means you can handle diverse input types in one request instead of juggling separate pipelines. The pricing structure makes it viable to run thousands of queries daily without blowing budgets—input costs are roughly one-tenth what you'd pay for GPT-4o or Claude Sonnet.
Trade-offs
Without public benchmarks we can't quantify reasoning or instruction-following against peers, but the price point signals this sits below frontier models on accuracy-sensitive tasks. Expect weaker performance on complex multi-step reasoning, nuanced creative writing, or edge cases requiring deep domain knowledge. Output costs at $2.50/Mtok are higher than input, so verbose responses eat into savings. If your use case demands the best possible answer quality or you're doing low-volume, high-stakes work, you'll likely need to step up to Claude Sonnet or GPT-4o.
Specifications
- Provider
- amazon
- Category
- llm
- Context length
- 1,000,000 tokens
- Max output
- 65,535 tokens
- Modalities
- text, image, video, file
- License
- proprietary
- Released
- 2025-12-02
Pricing
- Input
- $0.30/Mtok
- Output
- $2.50/Mtok
- Model ID
amazon/nova-2-lite-v1
Per-token prices show what the model costs upstream. On Switchy your team draws from one shared org credit pool - one plan, one balance for everyone.
Team cost calculator
5 seats · 80 msgs/day
Switchy meters this against your org's shared credit pool - one plan, one balance for everyone.
Providers
| Provider | Context | Input | Output | P50 latency | Throughput | 30d uptime |
|---|---|---|---|---|---|---|
| amazon | 1000k | $0.30/Mtok | $2.50/Mtok | — | — | — |
Performance
Benchmarks
Works well with
Top MCPs
Compatibility data comes from first-party telemetry; once we have enough co-usage signal, top MCPs for this model will appear here.
How Switchy teams use it
Starter prompts
Classify Support Tickets
Read the following support ticket and classify it into one of these categories: Billing, Technical Issue, Feature Request, Account Access, or Other. Provide only the category name and a one-sentence reason.Open in a Space →
Summarize Long Transcripts
Summarize the attached transcript in 200 words or less. Focus on decisions made, action items assigned, and unresolved questions. Use bullet points for clarity.Open in a Space →
Extract Data from Mixed Files
Extract the following fields from the attached document: invoice number, date, vendor name, line items with quantities and prices, and total amount. Return results as JSON.Open in a Space →
Moderate User-Generated Content
Review the attached content for violations of our community guidelines: hate speech, graphic violence, spam, or sexually explicit material. Respond with 'APPROVED' or 'FLAGGED' and a brief reason if flagged.Open in a Space →
Draft Routine Email Replies
Draft a polite email reply to the following customer inquiry. Acknowledge their question, provide a helpful answer based on the context below, and offer to escalate if needed. Keep it under 150 words.Open in a Space →
Example outputs
Illustrative - representative of the model's voice and quality, not literal recordings.
Review this 45-page quarterly financial report PDF and summarize the three biggest revenue shifts compared to last quarter, with specific percentage changes.
Based on the Q3 2024 report, three major revenue shifts stand out: (1) Cloud infrastructure services grew 34% quarter-over-quarter, driven primarily by enterprise migrations mentioned on pages 12-14. (2) Hardware sales declined 18%, attributed to supply chain delays and reduced consumer demand detailed in the operations section. (3) Subscription revenue increased 22%, with the CFO noting improved retention rates and upsell success in the mid-market segment. The report flags ongoing concerns about currency headwinds affecting international revenue by approximately 3-4 percentage points across all categories.
Nova 2 Lite's 1M token context window handles long documents efficiently at $0.30/Mtok input — significantly cheaper than alternatives for document analysis tasks. The multimodal file support means it can process native PDFs without conversion. However, without public benchmarks, accuracy on complex financial reasoning or numerical extraction remains unverified in production scenarios.
I'm attaching a 2-minute product demo video. Write a landing page hero section that captures the key features shown, optimized for conversion.
**Ship faster with visual feedback that actually works** Your design team sees changes in real-time. Your developers get pixel-perfect specs automatically. Your stakeholders approve mockups without endless email threads. Collaborate in one workspace where design files, code components, and feedback live together. No more screenshot tennis. No more "which version is final?" Trusted by teams at 2,000+ companies who ship products people love. [Start free trial] [Watch 60-sec demo]
Video input capability lets Nova 2 Lite extract visual information and translate it into marketing copy, which few models at this price point support. The output demonstrates concise, conversion-focused writing. Trade-off: without benchmark data on video understanding accuracy, it's unclear how reliably it captures nuanced visual details versus making reasonable inferences from context.
Here's a screenshot of an error message my user reported. Explain what's happening and give me the exact code fix for our Python Flask API.
The error shows a `KeyError: 'user_id'` in your `/api/profile` endpoint, triggered when the JWT token is missing the expected claim. This happens when users authenticate through the legacy OAuth flow, which doesn't include `user_id` in the token payload. Fix in `routes/profile.py`: ```python @app.route('/api/profile') @jwt_required() def get_profile(): claims = get_jwt() user_id = claims.get('user_id') or claims.get('sub') # fallback to 'sub' if not user_id: return jsonify({'error': 'Invalid token'}), 401 ``` This handles both token formats gracefully.
Image input plus code generation makes Nova 2 Lite practical for debugging workflows where engineers share screenshots. The $2.50/Mtok output pricing is competitive for code generation tasks. However, the lack of published coding benchmarks means you can't compare its accuracy against models like Claude or GPT-4 on standard evaluation sets before committing to it for production use.
Use-case deep-dives
When Nova 2 Lite wins on support ticket routing at scale
A 12-person e-commerce team processing 800+ support tickets daily needs fast classification without blowing the budget. Nova 2 Lite hits the sweet spot here: $0.30/Mtok input means you can feed full ticket histories (emails, chat logs, order data) into that 1M token context without worrying about cost, and the $2.50/Mtok output keeps auto-responses cheap when you're generating hundreds of replies per day. The multimodal support matters when customers attach screenshots of broken checkout flows or product defects—you route those to the right specialist without manual review. If your ticket volume drops below 200/day, the speed advantage over cheaper models stops mattering and you should just use GPT-4o mini. Above 500/day, Nova 2 Lite's input pricing becomes the deciding factor for keeping context-rich routing affordable.
Why Nova 2 Lite handles enterprise contract analysis better than alternatives
A 4-person legal ops team at a SaaS company needs to extract renewal dates, liability caps, and termination clauses from 60-page MSAs without chunking. Nova 2 Lite's 1M token window means you drop the entire contract plus your extraction template into a single call—no RAG pipeline, no context-stitching errors. At $0.30/Mtok input, processing a 50-page contract (roughly 40K tokens) costs about $0.012, which is negligible when you're doing 20-30 contracts per month. The multimodal capability handles scanned PDFs that come in as images, which is half your inbound volume in enterprise procurement. The output pricing at $2.50/Mtok stings if you're generating full summaries, so keep your extraction schema tight—structured JSON outputs under 2K tokens. If you need higher reasoning quality for ambiguous clauses, step up to Claude 3.5 Sonnet and eat the 10x cost increase.
When Nova 2 Lite's multimodal input makes video moderation economical
A 7-person creator platform moderates 400 hours of uploaded video weekly, flagging policy violations before content goes live. Nova 2 Lite's native video understanding means you can sample frames at 1fps, feed 60 seconds of context (roughly 15K tokens with frame embeddings), and get violation classifications without transcoding to text-only. At $0.30/Mtok input, processing a 2-minute video clip costs under $0.01, making real-time moderation feasible at scale. The 1M token context lets you include the creator's upload history and past strikes in the same call, improving accuracy on borderline cases. Output is cheap here—you're returning structured flags, not essays—so the $2.50/Mtok rate barely registers. If you're moderating under 50 hours/week, GPT-4o's superior reasoning on edge cases justifies the higher cost. Above 300 hours/week, Nova 2 Lite's input pricing becomes the only way to stay under $500/month on moderation.
Frequently asked
Is Amazon Nova 2 Lite good for general text tasks?
Yes, Nova 2 Lite handles everyday text work well — drafting emails, summarizing documents, basic Q&A. At $0.30/$2.50 per Mtok it's positioned as a budget option in Amazon's lineup. Without public benchmarks we can't compare it directly to GPT-4o or Claude, but the multimodal support and 1M token window make it versatile for mixed-content workflows where cost matters more than peak performance.
Is Nova 2 Lite cheaper than GPT-4o Mini?
Nova 2 Lite costs $0.30 input and $2.50 output per Mtok. GPT-4o Mini runs $0.15/$0.60 per Mtok — roughly 5× cheaper on input and 4× cheaper on output. If you're processing large volumes of text or generating long responses, GPT-4o Mini will cost significantly less. Nova 2 Lite's advantage is the 1M context window and native AWS integration, not price.
Can Nova 2 Lite process video files directly?
Yes, Nova 2 Lite accepts video as input alongside text, images, and files. The 1M token context window gives you room to work with longer clips or multiple videos in one request. Practical throughput depends on video length and resolution — expect each minute of video to consume thousands of tokens. Good for content moderation, scene analysis, or extracting metadata, less so for frame-by-frame precision work.
How does Nova 2 Lite compare to Nova 2 Pro?
Amazon hasn't published benchmarks for either model, so we're comparing on specs alone. Nova 2 Lite is the budget tier — lower cost, likely lower reasoning capability. Pro will handle harder logic, coding, and nuanced analysis better. If your task is straightforward summarization, classification, or content extraction, Lite saves money. For anything requiring multi-step reasoning or technical accuracy, test Pro first.
Should I use Nova 2 Lite for production chatbots?
It depends on your latency and quality requirements. The 1M context window lets you include full conversation history and knowledge base chunks without truncation. At $2.50/Mtok output, long responses add up fast compared to cheaper alternatives like Gemini Flash or GPT-4o Mini. Run a cost analysis on your average response length — if you're generating 500+ tokens per turn at scale, the output pricing becomes a bottleneck.