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. | 16B | 30B |
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. | 4k | 1M |
| API pricingUSD per 1M tokens · lower wins | ||
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. | — | $0.00Nvidia |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $0.00Nvidia |
| — | $11.00Darkbloom · int4 | |
| 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 has 16B parameters, while Nemotron 3.5 Lightning has 30B. Context windows are 4k (DeepSeek-MoE) vs 1M (Nemotron 3.5 Lightning). 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.