Nova Pro 1.0
2537°
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Amazon | 300,000 token context | $0.80/M input, $3.20/M output. Amazon Nova Pro 1.0 is a capable multimodal model from Amazon focused on providing a combination of accuracy, speed, and cost for a wide range of tasks. As of December 2024, it achieves state-of-the-art performance on key benchmarks including visual question answering (TextVQA) and video understanding (VATEX). Amazon Nova Pro demonstrates strong capabilities in processing both visual and textual information and at analyzing financial documents. NOTE: Video input is not supported at this time.
Guides for this model
Open weights vs open source vs API-only: what you are actually allowed to do
How to choose an AI model in October 2026: the closed source news, then the open weights worth downloading
The 10 cheapest ChatGPT alternatives in 2026: free local models, free tiers and flat-rate plans
Captain's notes
Notes from 2026-10-13
Nova Pro 1.0 is Amazon's mid-tier multimodal model, handling text and images across a 300,000-token context window at a price well below the frontier heavyweights. It posted state-of-the-art results on visual question answering and video understanding benchmarks at launch. It suits teams already in the AWS ecosystem who need solid multimodal performance without paying frontier prices.
Known for
- Strong visual question answering, competitive at launch on TextVQA.
- 300,000-token context window handles long documents comfortably.
- Notably good at analyzing financial documents with mixed text and tables.
- Competitive price: $0.80 per million input tokens, $3.20 per million output.
- Balances accuracy, speed and cost rather than chasing a single dimension.
Watch out for
- Video input is not supported at this time, despite video understanding appearing in benchmark claims.
- Closed weights, API-only — no local deployment option.
- Tied to Amazon's infrastructure; access runs through AWS Bedrock.
Prompts to try
Parse a financial table
I'm attaching a page from an annual report that contains a multi-year income statement. Extract revenue, operating income and net income for each year shown, present them in a markdown table, then note any line items that changed by more than 20% year over year and give a one-sentence explanation of each.
Long document digest
Here is a 200-page procurement contract. Identify the five most significant obligations placed on the vendor, the payment schedule, any penalty clauses, and the termination conditions. Summarise each in two sentences and flag anything that looks unusual compared with standard commercial contracts.
Image data extraction
I'm attaching a photograph of a handwritten lab notebook page. Transcribe all text and numerical values exactly as written, preserve the table structure if one exists, and flag any values that appear ambiguous or illegible.
Compare with
- Nova 2 LiteAPI-only model1,000,000 token context · $0.30/M input, $2.50/M output
- Qwen2.5 VL 72B InstructOpen-weights model128,000 token context · $0.80/M input, $1.00/M output
- Qwen3 VL 235B A22B InstructOpen-weights model262,144 token context · $0.21/M input, $1.90/M output
- Nova Lite 1.0API-only model300,000 token context · $0.06/M input, $0.24/M output
More text models from amazon
Questions people ask
- Can I run Nova Pro 1.0 locally?
- No. Amazon has not released the weights; the model is API-only, accessed through AWS Bedrock.
- What does Nova Pro 1.0 cost and how long is its context?
- It costs $0.80 per million input tokens and $3.20 per million output tokens, with a 300,000-token context window.
- How does Nova Pro compare to Nova Lite or Nova Micro?
- Nova Pro sits at the top of Amazon's Nova text and multimodal lineup, trading higher per-token cost for better accuracy and the full multimodal capability; Nova Lite and Micro are faster and cheaper but less capable.
Captain's verdictA sensible multimodal workhorse for AWS-native teams — honest pricing, long context, and real document-analysis chops, held back only by the closed-API constraint.
Captain writes these notes from the model's own description and model card. Prices and context sizes are the provider's at the time of writing and can change.
Ranking badge
Updated Oct 22, 2026
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How this score adds up
This model has no popularity data from any source yet, so it carries a stand-in number below 7,000° that keeps the lists complete. It never ranks above a model with data. The breakdown appears here as soon as a source reports it.
Glossary: the terms used here
- Heat score
- One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
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- Download-equivalents
- Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
- Log scale
- Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
- Likes
- Thumbs up and likes from every source, worth half a download each on the log scale.
- Adoption rate
- How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
- Measured and estimated
- Measured means two readings of a source exist and the difference is real. Estimated means only today's total is known and the past is spread over the model's life; the site says which one it is showing.
- Seeder
- Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
- AI Horde
- A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
- Generation sites
- Sites that host their own copies of a model and let people generate with it, such as PixAI, SeaArt and Yodayo. Their downloads count like Civitai's and each generation run as one download.
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- A text model served through an API, such as Claude or GPT, has no weights to download, so its usage is measured in tokens: the pieces of text it read and wrote through OpenRouter, a gateway many apps use, over the last 30 days. Every 10,000,000 tokens count as one download. Source: OpenRouter (openrouter.ai/rankings), CC BY 4.0.
- Full model (checkpoint)
- The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
- LoRA and embedding
- Small add-on files that steer someone else's weights toward a style, a character or a concept. They cannot run alone.
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- Degrees taken off for how long ago the family's weights came out: 150° a year, up to 750°. It keeps old downloads that had years to pile up from freezing the top of the list.
- Family boost
- A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
- Stand-in score
- A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
- New! (grace period)
- A model less than 7 days old shows New! instead of a score and holds no place in the rankings. Its score is computed from day one, but a model one day old grows faster than anything, so without the wait the week's #1 would always be whatever came out yesterday rather than what held up for a week.
- Trend
- How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
- Typical model
- The middle of the catalog: half the models with a figure grew faster over the period, half slower.
Nova Pro 1.0 is a text model for the Text / LLM family listed on ModelTrends.ai, a read-only catalog of open source AI image, video and text models. Compare it with other Text / LLM models and check its heat score to see how it is trending.
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