Compare AI models

Specifications
ParametersA rough measure of how big the model is. More parameters usually means more capable and more expensive to run, though it is a poor guide on its own — a smaller, newer model often beats a larger, older one.
—550B
API pricingUSD per 1M tokens · lower wins · base tier
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it.
$0.22—
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one.
$0.66—
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again.
$0.007—
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page.
$0.0144OpenInference$0.50DeepInfra
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
$0.18DeepInfra$2.20DeepInfra
$21.00DeepInfra · fp8$210DeepInfra · fp4
Benchmarks
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better.
39%49%
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better.
79%71.9%
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better.
82.7%56.4%
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better.
73.2%44.4%
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better.
34.8%26.7%
Overview
CompanyDeepSeekNVIDIA
Release dateJul 31 2026Jun 4 2026
AccessOpen WeightOpen Source
Model detailsView modelView model

Frequently asked questions

DeepSeek-V4-Flash-0731 leads Nemotron 3 Ultra on 4 of the 5 benchmarks they both report. Only DeepSeek-V4-Flash-0731 has a verified first-party API price: $0.22 per million input tokens and $0.66 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3 Ultra. Nemotron 3 Ultra shipped 57 days before DeepSeek-V4-Flash-0731, so benchmark comparisons should account for the intervening progress.

DeepSeek-V4-Flash-0731 is open weight, while Nemotron 3 Ultra is open source.

On BullshitBench v2, Nemotron 3 Ultra leads at 49% vs DeepSeek-V4-Flash-0731 at 39%. On SWE-Bench Verified, DeepSeek-V4-Flash-0731 leads at 79% vs Nemotron 3 Ultra at 71.9%. On Terminal-Bench 2.1, DeepSeek-V4-Flash-0731 leads at 82.7% vs Nemotron 3 Ultra at 56.4%. On BrowseComp, DeepSeek-V4-Flash-0731 leads at 73.2% vs Nemotron 3 Ultra at 44.4%. On Humanity's Last Exam · with tools, DeepSeek-V4-Flash-0731 leads at 34.8% vs Nemotron 3 Ultra at 26.7%.