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. | 7B/67B | — |
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 |
| 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. | — | 15% |
| Overview | ||
| Company | DeepSeek | |
| Release date | Nov 29 2023 | Jan 30 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek-LLMvsClaude Haiku 5.5Gemini 2.0 FlashvsClaude Haiku 5.5DeepSeek-LLMvsGPT-6.1 SolGemini 2.0 FlashvsGPT-6.1 SolDeepSeek-LLMvsMuse Spark OpenGemini 2.0 FlashvsMuse Spark OpenDeepSeek-LLMvsGrok 4.7Gemini 2.0 FlashvsGrok 4.7DeepSeek-LLMvsMistral Large 4Gemini 2.0 FlashvsMistral Large 4DeepSeek-LLMvsKimi K3Gemini 2.0 FlashvsKimi K3Frequently asked questions
DeepSeek-LLM and Gemini 2.0 Flash don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-LLM shipped 428 days before Gemini 2.0 Flash, so benchmark comparisons should account for the intervening progress.
Context windows are 4k (DeepSeek-LLM) vs 1M (Gemini 2.0 Flash). DeepSeek-LLM is open weight, while Gemini 2.0 Flash is closed.
Direct benchmark comparisons are unavailable — DeepSeek-LLM and Gemini 2.0 Flash don't publish scores on any of the same benchmarks.