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 | 256k |
| Overview | ||
| Company | Meta | SpaceXSI |
| Release date | Aug 24 2023 | Jul 9 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
Code LlamavsClaude Haiku 5.5Grok 4vsClaude Haiku 5.5Code LlamavsGPT-6.1 SolGrok 4vsGPT-6.1 SolCode LlamavsGemini 4 ArgonGrok 4vsGemini 4 ArgonCode LlamavsDeepSeek-V4.1-Flash-1017Grok 4vsDeepSeek-V4.1-Flash-1017Code LlamavsMistral Large 4Grok 4vsMistral Large 4Code LlamavsKimi K3Grok 4vsKimi K3Frequently asked questions
Code Llama and Grok 4 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 685 days before Grok 4, so benchmark comparisons should account for the intervening progress.
Context windows are 16k (Code Llama) vs 256k (Grok 4). Code Llama is open weight, while Grok 4 is closed.
Direct benchmark comparisons are unavailable — Code Llama and Grok 4 don't publish scores on any of the same benchmarks.