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 | 106B |
| 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. | — | $0.20 |
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. | — | $1.10 |
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. | — | $0.03 |
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. | — | $0.13Novita |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $0.85Novita |
| — | $68.50Novita · bf16 | |
| These models have no shared benchmark scores. | ||
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. | — | 59.8% |
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% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | 66.75% | — |
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% | — |
| Overview | ||
| Company | NVIDIA | Z.ai |
| Release date | Oct 15 2026 | Jul 28 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
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Nemotron 3.5 Bolt 74B and GLM-4.5-Air don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only GLM-4.5-Air has a verified first-party API price: $0.20 per million input tokens and $1.10 per million output tokens. No pay-as-you-go API rate is tracked for Nemotron 3.5 Bolt 74B. GLM-4.5-Air shipped 444 days before Nemotron 3.5 Bolt 74B, so benchmark comparisons should account for the intervening progress.
Nemotron 3.5 Bolt 74B has 74B parameters, while GLM-4.5-Air has 106B.
Direct benchmark comparisons are unavailable — Nemotron 3.5 Bolt 74B and GLM-4.5-Air don't publish scores on any of the same benchmarks.