Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 8B | — |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 64k | 1.05M |
| 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. | — | $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 | |
| These models have no shared benchmark scores. | ||
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | — | 89.3% |
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% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 94.4% |
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 23 2026 | Mar 5 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
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Nemotron 3.5 Bolt E4B 4GB and GPT-5.4-Pro don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. 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 E4B 4GB. GPT-5.4-Pro shipped 232 days before Nemotron 3.5 Bolt E4B 4GB, so benchmark comparisons should account for the intervening progress.
Context windows are 64k (Nemotron 3.5 Bolt E4B 4GB) vs 1.05M (GPT-5.4-Pro). Nemotron 3.5 Bolt E4B 4GB is open weight, while GPT-5.4-Pro is closed.
Direct benchmark comparisons are unavailable — Nemotron 3.5 Bolt E4B 4GB and GPT-5.4-Pro don't publish scores on any of the same benchmarks.