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. | 70B | 48B |
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. | 16k | 1M |
| Overview | ||
| Company | Meta | Moonshot AI |
| Release date | Jan 29 2024 | Oct 30 2025 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Code Llama 70BvsClaude Haiku 5.5Kimi LinearvsClaude Haiku 5.5Code Llama 70BvsGPT-6.1 SolKimi LinearvsGPT-6.1 SolCode Llama 70BvsGemini 4 ArgonKimi LinearvsGemini 4 ArgonCode Llama 70BvsGrok 4.7Kimi LinearvsGrok 4.7Code Llama 70BvsDeepSeek-V4.1-Flash-1017Kimi LinearvsDeepSeek-V4.1-Flash-1017Code Llama 70BvsMistral Large 4Kimi LinearvsMistral Large 4Frequently asked questions
Code Llama 70B and Kimi Linear don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama 70B shipped 640 days before Kimi Linear, so benchmark comparisons should account for the intervening progress.
Code Llama 70B has 70B parameters, while Kimi Linear has 48B. Context windows are 16k (Code Llama 70B) vs 1M (Kimi Linear).
Direct benchmark comparisons are unavailable — Code Llama 70B and Kimi Linear don't publish scores on any of the same benchmarks.