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. | 74B | — |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $30.00 |
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. | — | $180.00 |
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. | — | $15.00OpenAI |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $90.00OpenAI |
| — | $15,000OpenAI list price | |
| Benchmarks | ||
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | 66.75% | 89.3% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 86.43% | 94.4% |
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. | 50.98% | — |
MCP AtlasMulti-step tool use — Can the AI chain together many tools and steps to complete one bigger task, rather than doing just a single thing? Higher is better. | 52.2% | — |
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. | — | 58.7% |
ARC-AGI-2Abstract reasoning — Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | — | 83.3% |
FrontierMath · Tier 1–3Advanced math — Very hard, research-level math problems. Tiers 1–3 are the (still extremely difficult) lower tiers. Higher is better. | — | 50% |
FrontierMath · Tier 4Advanced math — Very hard, research-level math problems. Tier 4 is the hardest — close to what professional research mathematicians tackle. Higher is better. | — | 38% |
GDPval (win/tie rate)Knowledge work — How often the AI's work matches or beats a human expert's on real knowledge-work tasks. Higher is better. | — | 82% |
| Overview | ||
| Company | NVIDIA | OpenAI |
| Release date | Oct 15 2026 | Mar 5 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
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GPT-5.4-Pro leads Nemotron 3.5 Bolt 74B on 2 of the 2 benchmarks they both report (BrowseComp, GPQA Diamond). Only GPT-5.4-Pro has a verified first-party API price: $30.00 per million input tokens and $180.00 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3.5 Bolt 74B. GPT-5.4-Pro shipped 224 days before Nemotron 3.5 Bolt 74B, so benchmark comparisons should account for the intervening progress.
Nemotron 3.5 Bolt 74B is open weight, while GPT-5.4-Pro is closed.
On BrowseComp, GPT-5.4-Pro leads at 89.3% vs Nemotron 3.5 Bolt 74B at 66.75%. On GPQA Diamond, GPT-5.4-Pro leads at 94.4% vs Nemotron 3.5 Bolt 74B at 86.43%.