Llama 4 Maverick
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
BenchLM is tracking Llama 4 Maverick, but sourced benchmark results are not published on the site yet. This page currently shows the model metadata we can verify now, and score-level benchmark coverage will appear once public evaluations land.
Llama 4 Maverick is a open weight model with a 1M token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
This profile currently has 0 sourced benchmarks on BenchLM, so the benchmark sections below are intentionally marked as coming soon.
Its strongest category is Reasoning (#68), while its weakest is Instruction Following (#99). This performance profile makes it particularly strong for complex reasoning, multi-step problem solving, and analytical tasks.
Ranking Distribution
Category rank across 8 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
#91Coding
#81Reasoning
#68Knowledge
#86Math
#78Multilingual
#90Multimodal
#80Inst. Following
#99Chatbot Arena Performance
Benchmark Details
Only benchmark rows with an attached exact-source record are shown here. Source-unverified manual rows and generated rows are hidden from model pages.
Compare This Model
See how Llama 4 Maverick stacks up against similar models
Frequently Asked Questions
How does Llama 4 Maverick perform overall in AI benchmarks?
BenchLM is tracking Llama 4 Maverick, but sourced benchmark coverage is still coming soon. We currently list its creator, model type, and context window while we wait for public benchmark results.
Is Llama 4 Maverick open source?
Yes, Llama 4 Maverick is an open weight model created by Meta, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does Llama 4 Maverick have full benchmark coverage on BenchLM?
Not yet. Llama 4 Maverick currently has 0 published benchmark scores out of the 152 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of Llama 4 Maverick?
Llama 4 Maverick has a context window of 1M, which determines how much text it can process in a single interaction.
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