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Curated head-to-head

DeepSeek R1 vs Llama 4 Maverick

A workload-first comparison—not a universal winner. Review price, access, context, and evidence before choosing.

01 / Open weights
by DeepSeek

DeepSeek R1

A mixture-of-experts reasoning model released with permissive weights. R1 made high-end chain-of-thought style performance more accessible to self-hosted teams.

reasoningopen-weights
CONTEXT131K
LICENSEMIT
02 / Open weights
by Meta

Llama 4 Maverick

A natively multimodal mixture-of-experts model with a practical active parameter count and a million-token context window for self-hosted or managed deployments.

open-weightsmultimodal
CONTEXT1.0M
LICENSELlama 4 Community

The meaningful difference

R1 is centered on reasoning with an MIT license; Maverick is natively multimodal but uses Meta's community license.

Choose by workload

Choose DeepSeek R1 when your priority is permissively licensed reasoning and math. Its relevant strengths include permissive open-weight release and strong math and reasoning.

Choose Llama 4 Maverick when your priority is open-weight multimodal and long-context deployment. Account for community license is not osi-approved before committing.

Specification comparison

MeasureDeepSeek R1Llama 4 Maverick
AccessOpen weightsOpen weights
LicenseMITLlama 4 Community
Context131K1.0M
Provider-listed API input / 1M$0.55Unavailable
Provider-listed API output / 1M$2.19Unavailable
MMLU-Pro8480.5
GPQA Diamond71.569.8
SWE-bench Verified49.2—
LiveCodeBench65.943.4
SWE-Bench Pro——
Artificial Analysis Intelligence Index——

A fair test for this pair

Compare quantized deployments on identical hardware, recording memory, tokens per second, task quality, and license constraints.

Bottom line: use reported results to form a hypothesis, then make the decision with representative private tasks. Missing scores remain missing; no composite winner is manufactured.