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Nova Lite

Multimodal
Amazon

Affordable multimodal model providing ultra-fast processing of images, videos, documents, and text.

Key Specifications

Parameters
-
Context
300.0K
Release Date
November 20, 2024
Average Score
70.7%

Timeline

Key dates in the model's history
Announcement
November 20, 2024
Last Update
July 19, 2025
Today
March 25, 2026

Technical Specifications

Parameters
-
Training Tokens
-
Knowledge Cutoff
-
Family
-
Capabilities
MultimodalZeroEval

Pricing & Availability

Input (per 1M tokens)
$0.06
Output (per 1M tokens)
$0.24
Max Input Tokens
300.0K
Max Output Tokens
2.0K
Supported Features
Function CallingStructured OutputCode ExecutionWeb SearchBatch InferenceFine-tuning

Benchmark Results

Model performance metrics across various tests and benchmarks

General Knowledge

Tests on general knowledge and understanding
MMLU
0-shot chain-of-thought AI: 0-shotSelf-reported
80.5%

Programming

Programming skills tests
HumanEval
pass@1 n k pass@1 100% (accuracy), k/n, pass@1 : 1. 1 n, : ? 2. 1 k/n, pass@kSelf-reported
85.4%

Mathematics

Mathematical problems and computations
GSM8k
0-shot CoT thinking. thinkingSelf-reported
94.5%
MATH
0-shot CoT Chain-of-thought (CoT) - LLM "" ": ...". CoT accuracy LLM, CoT (0-shot) few-shot CoT, 0-shot CoTSelf-reported
73.3%

Reasoning

Logical reasoning and analysis
DROP
1. : "0-shot", "few-shot", 2. : 3. : 4. : 5. : 6. : 7. :Self-reported
80.2%
GPQA
6-shot CoT chain-of-thought () 6 (), thinking : 1. 2. 3. 6-shotSelf-reported
42.0%

Multimodal

Working with images and visual data
ChartQA
relaxed accuracySelf-reported
86.8%
DocVQA
ANLS (ANLS) "", ANLS (NLD). NLD high ANLS (0.5) ANLS NLD (1-NLD, NLD < 0.5, 0), ANLSSelf-reported
92.4%
MMMU
CoT accuracy accuracy (CoT). ": []". (). CoTSelf-reported
56.2%

Other Tests

Specialized benchmarks
ARC-C
0-shot chain-of-thought AI: Chain-of-thought (CoT) — Standard CoT — (few-shot CoT). 0-shot CoT — CoT, "" ""Self-reported
92.4%
BBH
3-shot CoT "" (3-shot Chain of Thought, CoT) — LLM (Chain of Thought) (1-shot), 3-shot CoTSelf-reported
82.4%
BFCL
accuracySelf-reported
66.6%
CRAG
accuracySelf-reported
43.8%
EgoSchema
accuracySelf-reported
71.4%
FinQA
0-shot accuracySelf-reported
73.6%
GroundUI-1K
accuracySelf-reported
80.2%
IFEval
0-shot CoT "" "". thinkingSelf-reported
89.7%
LVBench
accuracySelf-reported
40.4%
MM-Mind2Web
accuracySelf-reported
60.7%
SQuALITY
ROUGE-L — (LCS). ROUGE, n-ROUGE-L ROUGE-L F-LCS: - Accuracy: LCS, : LCS, F-: ROUGE-LSelf-reported
19.2%
TextVQA
weighted accuracySelf-reported
80.2%
Translation en→Set1 COMET22
COMET22 COMET22. COMET22 — ATOMIC — — "PersonX ", — "xEffect", — "PersonX ", "PersonX " "PersonX "Self-reported
88.8%
Translation en→Set1 spBleu
spBleu spBleu — BLEU, BLEU spBleu : : 1. 2. 3. n-4. n-5. BLEUSelf-reported
41.5%
Translation Set1→en COMET22
COMET22 Gopher22 COMET22 — Gopher22, STEM, "" : 1. 2. 3. 4. COMET22Self-reported
88.8%
Translation Set1→en spBleu
spBleu spBleu, BLEU (Bilingual Evaluation Understudy), BLEU, spBleu BLEU spBleu BLEU, spBleu. spBleuSelf-reported
43.1%
VATEX
CIDEr CIDEr (Consensus-based Image Description Evaluation). CIDEr TF-IDF (Term Frequency-Inverse Document Frequency) n-n-n-TF-IDF n-(1 4). CIDEr evaluationSelf-reported
77.8%
VisualWebBench
accuracySelf-reported
77.7%

License & Metadata

License
proprietary
Announcement Date
November 20, 2024
Last Updated
July 19, 2025

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