Grok 3 Mini vs Llama 4 Maverick

Grok 3 Mini wins on 6 benchmarks, ties on 6, and loses none. Here's what that looks like in practice:

Tool Calling (5 vs no score for Maverick): Grok 3 Mini scores 5/5 on function selection, argument accuracy, and sequencing — tied for 1st among 54 models. Maverick's tool calling result was invalidated by a rate limit error during testing (noted in our data as a transient 429 from OpenRouter on 2026-04-13), so we cannot compare directly. For agentic workflows and API orchestration, Grok 3 Mini is the verified choice.

Faithfulness (5 vs 4): Grok 3 Mini scores 5/5 (tied for 1st among 55 models, alongside 32 others); Maverick scores 4/5 (rank 34 of 55). In RAG and summarization tasks — where sticking to source material without hallucinating is critical — Grok 3 Mini has a meaningful edge.

Strategic Analysis (3 vs 2): Grok 3 Mini scores 3/5 (rank 36 of 54); Maverick scores 2/5 (rank 44 of 54). Neither is strong here, but Grok 3 Mini is clearly better at nuanced tradeoff reasoning with real numbers.

Constrained Rewriting (4 vs 3): Grok 3 Mini scores 4/5 (rank 6 of 53); Maverick scores 3/5 (rank 31 of 53). Compressing content within hard character limits is a clear Grok 3 Mini advantage.

Classification (4 vs 3): Grok 3 Mini scores 4/5 (tied for 1st among 53 models, alongside 29 others); Maverick scores 3/5 (rank 31 of 53). For routing and categorization tasks, Grok 3 Mini is more reliable.

Long Context (5 vs 4): Grok 3 Mini scores 5/5 on retrieval accuracy at 30K+ tokens (tied for 1st among 55 models). Maverick scores 4/5 (rank 38 of 55). Ironically, despite Maverick having an 8x larger context window, Grok 3 Mini performs better within the range our tests cover.

Ties (6 benchmarks): Both models score identically on structured output (4), creative problem solving (3), safety calibration (2), persona consistency (5), agentic planning (3), and multilingual (4). Neither has an edge on these dimensions.

Context window is a separate consideration from benchmark performance: Maverick's 1,048,576-token window dwarfs Grok 3 Mini's 131,072 tokens. If your application genuinely requires processing documents at that scale, Maverick is the only option here. Maverick also supports image inputs (text+image→text), which Grok 3 Mini does not — a meaningful architectural difference for multimodal use cases.

Grok 3 Mini costs $0.30 per million input tokens and $0.50 per million output tokens. Llama 4 Maverick costs $0.15 per million input tokens and $0.60 per million output tokens. The gap flips depending on your token mix. At 1M tokens/month with a 50/50 input-output split, Grok 3 Mini runs about $0.40 versus Maverick's $0.375 — nearly identical. At 10M tokens/month, that's roughly $4,000 vs $3,750. At 100M tokens/month, you're looking at $40,000 vs $37,500. Maverick is cheaper on input-heavy workloads (e.g., document analysis, RAG pipelines where you feed large contexts but generate short outputs), while Grok 3 Mini becomes relatively cheaper on output-heavy workloads (e.g., long-form generation). The price ratio is 0.83 — close enough that benchmark performance and capability fit should drive your choice, not cost.

Choose Grok 3 Mini if your priority is benchmark-verified reliability across tool calling, faithfulness, classification, strategic analysis, and constrained rewriting — particularly for agentic pipelines, RAG systems, and content processing tasks where accuracy to source material matters. Its reasoning token support (with accessible thinking traces via include_reasoning) makes it well-suited for logic-intensive tasks where you want to audit the model's chain of thought.

Choose Llama 4 Maverick if you need multimodal inputs (images alongside text), require a context window exceeding 131K tokens, or are building a system that benefits from Meta's MoE architecture. Just note that several benchmark results favor Grok 3 Mini, so you're trading measurable capability on some dimensions for architectural features Grok 3 Mini doesn't offer.