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 | 128k |
| Overview | ||
| Company | Meta | OpenAI |
| Release date | Aug 24 2023 | Feb 12 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
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Code Llama and GPT-5.3-Codex-Spark don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama shipped 903 days before GPT-5.3-Codex-Spark, so benchmark comparisons should account for the intervening progress.
Context windows are 16k (Code Llama) vs 128k (GPT-5.3-Codex-Spark). Code Llama is open weight, while GPT-5.3-Codex-Spark is closed.
Direct benchmark comparisons are unavailable — Code Llama and GPT-5.3-Codex-Spark don't publish scores on any of the same benchmarks.