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. | 32k | 16k |
| Overview | ||
| Company | Meta | |
| Release date | Feb 8 2024 | Aug 24 2023 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemini 1.0 UltravsClaude Haiku 5.5Code LlamavsClaude Haiku 5.5Gemini 1.0 UltravsGPT-6.1 SolCode LlamavsGPT-6.1 SolGemini 1.0 UltravsGrok 4.7Code LlamavsGrok 4.7Gemini 1.0 UltravsDeepSeek-V4.1-Flash-1017Code LlamavsDeepSeek-V4.1-Flash-1017Gemini 1.0 UltravsMistral Large 4Code LlamavsMistral Large 4Gemini 1.0 UltravsKimi K3Code LlamavsKimi K3Frequently asked questions
Gemini 1.0 Ultra and Code Llama don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 168 days before Gemini 1.0 Ultra, so benchmark comparisons should account for the intervening progress.
Context windows are 32k (Gemini 1.0 Ultra) vs 16k (Code Llama). Gemini 1.0 Ultra is closed, while Code Llama is open weight.
Direct benchmark comparisons are unavailable — Gemini 1.0 Ultra and Code Llama don't publish scores on any of the same benchmarks.