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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.
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.
16k200k
API pricingUSD per 1M tokens · lower wins
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page.
—$1.10OpenAI
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input.
—$4.40OpenAI
—$440OpenAI
Overview
CompanyMetaOpenAI
Release dateJan 29 2024Apr 16 2025
AccessOpen WeightClosed
Model detailsView modelView model

Other comparisons

Code Llama 70BvsClaude Haiku 5.5o4-mini-highvsClaude Haiku 5.5Code Llama 70BvsGemini 4 Argono4-mini-highvsGemini 4 ArgonCode Llama 70BvsGrok 4.7o4-mini-highvsGrok 4.7Code Llama 70BvsDeepSeek-V4.1-Flash-1017o4-mini-highvsDeepSeek-V4.1-Flash-1017Code Llama 70BvsMistral Large 4o4-mini-highvsMistral Large 4Code Llama 70BvsKimi K3o4-mini-highvsKimi K3

Frequently asked questions

Code Llama 70B and o4-mini-high don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Code Llama 70B shipped 443 days before o4-mini-high, so benchmark comparisons should account for the intervening progress.

Context windows are 16k (Code Llama 70B) vs 200k (o4-mini-high). Code Llama 70B is open weight, while o4-mini-high is closed.

Direct benchmark comparisons are unavailable — Code Llama 70B and o4-mini-high don't publish scores on any of the same benchmarks.