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/13B/34B | — |
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 | 2M |
| Overview | ||
| Company | Meta | SpaceXSI |
| Release date | Aug 24 2023 | Sep 19 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Code LlamavsClaude Haiku 5.5Grok 4 FastvsClaude Haiku 5.5Code LlamavsGPT-6.1 SolGrok 4 FastvsGPT-6.1 SolCode LlamavsGemini 4 ArgonGrok 4 FastvsGemini 4 ArgonCode LlamavsDeepSeek-V4.1-Flash-1017Grok 4 FastvsDeepSeek-V4.1-Flash-1017Code LlamavsMistral Large 4Grok 4 FastvsMistral Large 4Code LlamavsKimi K3Grok 4 FastvsKimi K3Frequently asked questions
Code Llama and Grok 4 Fast don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 757 days before Grok 4 Fast, so benchmark comparisons should account for the intervening progress.
Context windows are 16k (Code Llama) vs 2M (Grok 4 Fast). Code Llama is open weight, while Grok 4 Fast is closed.
Direct benchmark comparisons are unavailable — Code Llama and Grok 4 Fast don't publish scores on any of the same benchmarks.