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 | 314B |
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 | 8k |
| Overview | ||
| Company | Meta | SpaceXSI |
| Release date | Aug 24 2023 | Nov 3 2023 |
| Access | Open Weight | Open Weight |
| Model details | View model | View model |
Other comparisons
Code LlamavsClaude Haiku 5.5Grok‑1vsClaude Haiku 5.5Code LlamavsGPT-6.1 SolGrok‑1vsGPT-6.1 SolCode LlamavsGemini 4 ArgonGrok‑1vsGemini 4 ArgonCode LlamavsDeepSeek-V4.1-Flash-1017Grok‑1vsDeepSeek-V4.1-Flash-1017Code LlamavsMistral Large 4Grok‑1vsMistral Large 4Code LlamavsKimi K3Grok‑1vsKimi K3Frequently asked questions
Code Llama and Grok‑1 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 71 days before Grok‑1, so benchmark comparisons should account for the intervening progress.
Code Llama has 7B/13B/34B parameters, while Grok‑1 has 314B. Context windows are 16k (Code Llama) vs 8k (Grok‑1).
Direct benchmark comparisons are unavailable — Code Llama and Grok‑1 don't publish scores on any of the same benchmarks.