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. | 8B | 70B |
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. | 1M | 16k |
| Overview | ||
| Company | Meta | |
| Release date | Oct 3 2024 | Jan 29 2024 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Gemini 1.5 Flash-8BvsClaude Haiku 5.5Code Llama 70BvsClaude Haiku 5.5Gemini 1.5 Flash-8BvsGPT-6.1 SolCode Llama 70BvsGPT-6.1 SolGemini 1.5 Flash-8BvsGrok 4.7Code Llama 70BvsGrok 4.7Gemini 1.5 Flash-8BvsDeepSeek-V4.1-Flash-1017Code Llama 70BvsDeepSeek-V4.1-Flash-1017Gemini 1.5 Flash-8BvsMistral Large 4Code Llama 70BvsMistral Large 4Gemini 1.5 Flash-8BvsKimi K3Code Llama 70BvsKimi K3Frequently asked questions
Gemini 1.5 Flash-8B and Code Llama 70B don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama 70B shipped 248 days before Gemini 1.5 Flash-8B, so benchmark comparisons should account for the intervening progress.
Gemini 1.5 Flash-8B has 8B parameters, while Code Llama 70B has 70B. Context windows are 1M (Gemini 1.5 Flash-8B) vs 16k (Code Llama 70B). Gemini 1.5 Flash-8B is closed, while Code Llama 70B is open weight.
Direct benchmark comparisons are unavailable — Gemini 1.5 Flash-8B and Code Llama 70B don't publish scores on any of the same benchmarks.