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 | 2.8T |
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 |
| Overview | ||
| Company | DeepSeek | Moonshot AI |
| Release date | Feb 5 2024 | Oct 23 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
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DeepSeek-Math and Kimi K3.1 Pro Highspeed don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-Math shipped 991 days before Kimi K3.1 Pro Highspeed, so benchmark comparisons should account for the intervening progress.
DeepSeek-Math has 7B parameters, while Kimi K3.1 Pro Highspeed has 2.8T. Context windows are 4k (DeepSeek-Math) vs 1M (Kimi K3.1 Pro Highspeed). DeepSeek-Math is open weight, while Kimi K3.1 Pro Highspeed is closed.
Direct benchmark comparisons are unavailable — DeepSeek-Math and Kimi K3.1 Pro Highspeed don't publish scores on any of the same benchmarks.