[whatmodel.sh](../../README.md) / Nova Lite
# Nova Lite
Amazon · released 2024-12 · closed weights
**score 49.7** ±1.9 · #376 of 732 · from 8 benchmark results across 4 sources
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks Nova Lite among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃●█▄▅▅▄▄▂▁ #243 of 313 31% 4
chat & writing ▁▁▁▃▆▄●█▆▇▇▃ #271 of 402* 39% 1
vision & documents ▁▁▂●▁▃▄▂▆▇█▄ #135 of 153* 26% 1
agent tasks · #243 of 313 · 31% of its score
Beats [o3-mini](o3-mini.md), [Llama 4 Maverick (402B-A17B)](llama-4-maverick.md), [DeepSeek R1 0528 Qwen3 8B](deepseek-r1-0528-qwen3-8b.md) here, though they rank higher overall. Trails [SmolLM3 3B](smollm3-3b.md), [Phi-3.5-mini-instruct](phi-3-5-mini-instruct.md), [Jamba 1.5 Mini](jamba-1-5-mini.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
BFCL v3 55.9% ▁▁▁▁▁▃▅●▅▄▁▁ beats 60/114 medium · avg 51% 8.7% blunt · at its level
BFCL V4 (2025-11-03 archive, mode… 33.2% ▃··●▃▃·▅·▃·█ beats 1/10 hard · avg 33% 8.0% at its level
Galileo Agent Leaderboard v1 (too… 86.8% ▃▃▃▃▆▅●▅█▂▅▂ beats 16/31 easy · avg 78% 7.8% typical
Galileo Agent Leaderboard v2 (act… 16.0% ●▃·▃▃▅▅█▃█▅▅ beats 0/19 hard · avg 26% 6.3% at its level
chat & writing · #271 of 402 · 39% of its score
Beats [Ministral 3 14B Reasoning 2512](ministral-3-14b-reasoning.md), [Ministral 3 14B](ministral-3-14b.md), [OpenThinker2 32B](openthinker2-32b.md) here, though they rank higher overall. Trails [Flan-T5 XXL](flan-t5-xxl.md), [North Micro Vision Instruct (2.4B)](north-micro-vision-instruct.md), [Granite 4.0 H 1B](granite-4-0-h-1b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LMArena (text) 1260.4 ▁▁▁▂▃▃●▆▆▇█▃ beats 94/385 avg 1260 39% blunt
vision & documents · #135 of 153 · 26% of its score
Trails [Qwen2-VL 7B Instruct](qwen2-vl-7b.md), [Qwen3.5 2B](qwen3-5-2b.md), [InternVL2-26B](internvl2-26b.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
Arena vision (style controlled) 1018.8 ▁▁▂●▂▂▃▄▅▅█▇ beats 15/152 avg 1061 26% blunt
other tests (2)
test result vs the others in its run difficulty counts why
Vectara hallucination leaderboard… 98.2% ▁▁▂▃▄▄█▆▃●▂▁ beats 126/140 very easy · avg 94% 2.5% blunt · maxed out · noisy
Vectara hallucination leaderboard… 93.9% ▁▂▁▂▅█▂▃●▃▁▁ beats 77/98 very easy · avg 90% 0.0% blunt
source results share of the score
LMArena leaderboard dataset 2 65% ▇▇▇▇▇▇▇▇
Berkeley Function Calling Leaderboard r… 2 17% ▇▇
Galileo Agent Leaderboard 2 14% ▇▇
Vectara hallucination leaderboard 2 3% ▇
prior: pull toward the middle 2% ▇
weighted average = 49.7
Licences: LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) · Berkeley Function Calling Leaderboard result archive ([Apache-2.0](../../licenses/bfcl-result-archive-v4-Apache-2.0.txt)) · Galileo Agent Leaderboard ([Apache-2.0](../../licenses/galileo-agent-leaderboard-Apache-2.0.txt)) · Vectara hallucination leaderboard ([Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0))
## How to run it
### Through an API
api (Amazon Bedrock) · $0.10/M blended · $0.06 in / $0.24 out per 1M tokens · [docs.aws.amazon.com](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-amazon-nova-lite.html)
[price source](https://aws.amazon.com/nova/pricing): USD per 1M tokens, Standard tier, geo cross-Region inference and in-Region, US East (N. Virginia). Amazon Nova Lite (amazon.nova-lite-v1:0). Observed 2026-09-28 (page price data $0.00006/$0.00024 per 1K tokens). · [context source](https://docs.aws.amazon.com/nova/latest/userguide/what-is-nova.html): Context limit from the maker's documentation, observed 2026-10-06.
[interactive version](https://whatmodel.sh/model/nova-lite) · [JSON](https://whatmodel.sh/api?format=json&all=1)