Llama 4 Maverick vs Llama 3.3 70B Instruct
Llama 4 against the 3.3 workhorse a huge install base still runs.
What the numbers say
- Llama 3.3 70B Instruct is about 1.9x cheaper on output tokens (3.5 vs 6.6 credits per 1M).
- Llama 4 Maverick takes noticeably more context: 1.0M vs 131K tokens.
- Llama 4 Maverick accepts images; Llama 3.3 70B Instruct is text-only.
- Llama 4 Maverick is the newer release (April 2025 vs December 2024).
Derived from the live registry Zeplik routes and bills against. Credits: 1 credit = $0.10, raw provider rate with a 1.10x margin.
Side by side
Llama 4 Maverick
Meta
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...
- Provider
- Meta
- Context window
- 1.0M tokens
- Input price
- 1.7 credits / 1M tokens ($0.15 raw)
- Output price
- 6.6 credits / 1M tokens ($0.60 raw)
- Vision (image input)
- Yes
- Tool calling
- Yes
- Extended reasoning
- No
Best for
- Everyday chat and drafting on an open-weight model with transparent lineage
- Very long documents and codebases: a 1.0M-token window fits entire books or repositories in one conversation
- Working with images: screenshots, charts, photos and scanned documents alongside text
- Tool use and agents: reliably calls functions, so it can search, run skills and drive workflows
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...
- Provider
- Meta
- Context window
- 131K tokens
- Input price
- 1.1 credits / 1M tokens ($0.10 raw)
- Output price
- 3.5 credits / 1M tokens ($0.32 raw)
- Vision (image input)
- No
- Tool calling
- Yes
- Extended reasoning
- No
Best for
- Everyday chat and drafting on an open-weight model with transparent lineage
- Tool use and agents: reliably calls functions, so it can search, run skills and drive workflows
Try both on Zeplik
The honest answer to most model debates is to run your own prompt on both. Zeplik puts Llama 4 Maverick and Llama 3.3 70B Instruct in the same chat, so you can switch mid-conversation and compare answers on the work you actually do.