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 | 284B |
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. | — | $0.0113OpenInference |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $0.0226OpenInference |
| — | $3.39OpenInference · fp4 | |
| These models have no shared benchmark scores. | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 18% |
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | — | 91.6% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 88.1% |
| Overview | ||
| Company | DeepSeek | DeepSeek |
| Release date | Jan 11 2024 | Apr 24 2026 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
DeepSeek-MoEvsClaude Haiku 5.5DeepSeek-V4-FlashvsClaude Haiku 5.5DeepSeek-MoEvsGPT-6.1 SolDeepSeek-V4-FlashvsGPT-6.1 SolDeepSeek-MoEvsGemini 4 ArgonDeepSeek-V4-FlashvsGemini 4 ArgonDeepSeek-MoEvsMuse Spark OpenDeepSeek-V4-FlashvsMuse Spark OpenDeepSeek-MoEvsGrok 4.7DeepSeek-V4-FlashvsGrok 4.7DeepSeek-MoEvsMistral Large 4DeepSeek-V4-FlashvsMistral Large 4Frequently asked questions
DeepSeek-MoE and DeepSeek-V4-Flash don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-MoE shipped 834 days before DeepSeek-V4-Flash, so benchmark comparisons should account for the intervening progress.
DeepSeek-MoE has 16B parameters, while DeepSeek-V4-Flash has 284B. Context windows are 4k (DeepSeek-MoE) vs 1M (DeepSeek-V4-Flash).
Direct benchmark comparisons are unavailable — DeepSeek-MoE and DeepSeek-V4-Flash don't publish scores on any of the same benchmarks.