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/67B | — |
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. | 4k | 128k |
| Overview | ||
| Company | DeepSeek | OpenAI |
| Release date | Nov 29 2023 | Feb 12 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek-LLMvsClaude Haiku 5.5GPT-5.3-Codex-SparkvsClaude Haiku 5.5DeepSeek-LLMvsGemini 4 ArgonGPT-5.3-Codex-SparkvsGemini 4 ArgonDeepSeek-LLMvsMuse Spark OpenGPT-5.3-Codex-SparkvsMuse Spark OpenDeepSeek-LLMvsGrok 4.7GPT-5.3-Codex-SparkvsGrok 4.7DeepSeek-LLMvsMistral Large 4GPT-5.3-Codex-SparkvsMistral Large 4DeepSeek-LLMvsKimi K3GPT-5.3-Codex-SparkvsKimi K3Frequently asked questions
DeepSeek-LLM 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. DeepSeek-LLM shipped 806 days before GPT-5.3-Codex-Spark, so benchmark comparisons should account for the intervening progress.
Context windows are 4k (DeepSeek-LLM) vs 128k (GPT-5.3-Codex-Spark). DeepSeek-LLM is open weight, while GPT-5.3-Codex-Spark is closed.
Direct benchmark comparisons are unavailable — DeepSeek-LLM and GPT-5.3-Codex-Spark don't publish scores on any of the same benchmarks.