whatmodel.sh / Nova 2 Omni (Preview)
Nova 2 Omni (Preview)
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Nova 2 Omni (Preview) is a closed-weights language model from Amazon, released November 2025.
$ how it compares
The LLMs ranked either side of Nova 2 Omni (Preview), out of 1132 with a score, then more from Amazon.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 165 |  xLAM-2-32b-fc-r | 66±4 | local | ||
| 166 |  o4-mini | 66±1 | api $1.93/M | ||
| 167 | Nova 2 Omni (Preview) | 66±7 | api $0.93/M | ||
| 168 | GPT-5.1-Codex | 66±2 | comparison only | ||
| 169 |  Grok 3 Preview (02-24) | 66±3 | comparison only | ||
| more from Amazon | |||||
| 134 |  Amazon Nova Experimental Chat (26-02-10) | 68±3 | comparison only | ||
| 162 | Amazon Nova Experimental Chat (26-01-10) | 67±3 | comparison only | ||
| 206 | Amazon Nova Experimental Chat (12-10) | 64±3 | comparison only | ||
$ what it's good at
agent tasks▁▁▃▆█▆▅▄▄▃▂▁ #105 of 334 * · 80% of its score · 1 test
Beats Grok 4.20 (0309 reasoning), Grok 4.3, o3-pro here, though they rank higher overall. Trails SmolLM3 3B, Nova 2 Pro (Preview), Mistral Medium 3.5 (128B) here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| τ²-Bench-Verified (GPT-5.1 user) lab | 75.7% ✎ | ▂··▄···▂▄▄█▄ beats 6/13 | 80% |
$ where to run it
Through an API
api · Amazon Bedrock · $0.92/M · $0.3 in / $2.8 out per 1M tokens · 1M context · aws.amazon.com ↗ · price sourceUSD per 1M tokens: text input and text output, Amazon Bedrock Standard tier, geo cross-Region inference and in-Region, Amazon Nova 2 Omni (Preview). Audio input and image output are priced differently; global cross-Region inference is listed lower. Page table values are rendered from AWS's own price data file for the page (b0.p.awsstatic.com meteredUnitMaps, bedrock USD, published 2026-09-25T06:55:02Z); US East (N. Virginia) selected. Priority/Flex/Batch tiers, cached tokens and non-text modalities excluded. Currency: USD. AWS official Amazon Nova pricing page, observed 2026-09-25.
$ how the score was worked out · Amazon AGI — τ²-Bench-Verified 80%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
 Amazon AGI — τ²-Bench-Verified · lab-reported | 1 | 80% |
| prior · pull toward the middle | 20% | |
| weighted average | = 66.3 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json