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 |
| 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. | — | $0.25 |
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. | — | $1.50 |
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. | — | $0.025 |
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. | — | $0.125Google AI Studio |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $0.75Google AI Studio |
| — | $125Google list price | |
| 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. | — | 11% |
| Overview | ||
| Company | DeepSeek | |
| Release date | Nov 29 2023 | Mar 3 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek-LLMvsClaude Haiku 5.5Gemini 3.1 Flash-LitevsClaude Haiku 5.5DeepSeek-LLMvsGPT-6.1 SolGemini 3.1 Flash-LitevsGPT-6.1 SolDeepSeek-LLMvsMuse Spark OpenGemini 3.1 Flash-LitevsMuse Spark OpenDeepSeek-LLMvsGrok 4.7Gemini 3.1 Flash-LitevsGrok 4.7DeepSeek-LLMvsMistral Large 4Gemini 3.1 Flash-LitevsMistral Large 4DeepSeek-LLMvsKimi K3Gemini 3.1 Flash-LitevsKimi K3Frequently asked questions
DeepSeek-LLM and Gemini 3.1 Flash-Lite don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only Gemini 3.1 Flash-Lite has a verified first-party API price: $0.25 per million input tokens and $1.50 per million output tokens. No pay-as-you-go API rate is tracked for DeepSeek-LLM. DeepSeek-LLM shipped 825 days before Gemini 3.1 Flash-Lite, so benchmark comparisons should account for the intervening progress.
Context windows are 4k (DeepSeek-LLM) vs 1M (Gemini 3.1 Flash-Lite). DeepSeek-LLM is open weight, while Gemini 3.1 Flash-Lite is closed.
Direct benchmark comparisons are unavailable — DeepSeek-LLM and Gemini 3.1 Flash-Lite don't publish scores on any of the same benchmarks.