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. | 70B | — |
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. | 128k | 1.05M |
| 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 | |
| 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 15 2024 | Mar 5 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
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Llama 3.1 Nemotron 70B 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 Llama 3.1 Nemotron 70B. Llama 3.1 Nemotron 70B shipped 506 days before GPT-5.4-Pro, so benchmark comparisons should account for the intervening progress.
Context windows are 128k (Llama 3.1 Nemotron 70B) vs 1.05M (GPT-5.4-Pro). Llama 3.1 Nemotron 70B is open weight, while GPT-5.4-Pro is closed.
Direct benchmark comparisons are unavailable — Llama 3.1 Nemotron 70B and GPT-5.4-Pro don't publish scores on any of the same benchmarks.