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. | — | 30B |
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | — | 1M |
| API pricingUSD per 1M tokens · lower wins | ||
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $0.039Darkbloom |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $0.16DeepInfra |
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. | — | 51.6% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 75.4% |
| Overview | ||
| Company | DeepSeek | NVIDIA |
| Release date | Jan 11 2024 | Aug 11 2026 |
| Access | Open Weight | Open Source |
| Model details | View model | View model |
Other comparisons
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DeepSeek-MoE and Nemotron 3.5 Lightning don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-MoE shipped 943 days before Nemotron 3.5 Lightning, so benchmark comparisons should account for the intervening progress.
DeepSeek-MoE is open weight, while Nemotron 3.5 Lightning is open source.
Direct benchmark comparisons are unavailable — DeepSeek-MoE and Nemotron 3.5 Lightning don't publish scores on any of the same benchmarks.