Grok 4 vs Llama 4 Maverick

Across our 12-test suite, Grok 4 outscores Llama 4 Maverick on 7 tests, ties on 5, and loses none. Here's the test-by-test breakdown:

Strategic Analysis (5 vs 2): This is the widest gap in the comparison. Grok 4 scores 5/5 (tied for 1st among 54 models), while Llama 4 Maverick scores 2/5 (rank 44 of 54). For tasks requiring nuanced tradeoff reasoning with real numbers — investment analysis, competitive strategy, policy evaluation — this gap is operationally significant.

Faithfulness (5 vs 4): Grok 4 scores 5/5 (tied for 1st among 55 models); Llama 4 Maverick scores 4/5 (rank 34 of 55). In summarization and RAG workflows where sticking to source material matters, Grok 4 has a measurable edge.

Multilingual (5 vs 4): Grok 4 scores 5/5 (tied for 1st among 55 models); Llama 4 Maverick scores 4/5 (rank 36 of 55). Products serving non-English markets will see a quality difference.

Long Context (5 vs 4): Grok 4 scores 5/5 (tied for 1st among 55 models); Llama 4 Maverick scores 4/5 (rank 38 of 55). Both support large context windows — Llama 4 Maverick's is actually larger at 1,048,576 tokens vs Grok 4's 256,000 — but Grok 4 retrieves more accurately at 30K+ tokens in our testing.

Constrained Rewriting (4 vs 3): Grok 4 scores 4/5 (rank 6 of 53); Llama 4 Maverick scores 3/5 (rank 31 of 53). Compression tasks with hard character limits favor Grok 4.

Classification (4 vs 3): Grok 4 scores 4/5 (tied for 1st among 53 models); Llama 4 Maverick scores 3/5 (rank 31 of 53). Routing and categorization tasks favor Grok 4.

Tool Calling (4 vs not scored): Grok 4 scores 4/5 (rank 18 of 54). Llama 4 Maverick has no tool calling score in our data — the test hit a rate limit error on OpenRouter during our testing period, which the payload flags as likely transient. We cannot compare these two on tool calling from our data alone.

Ties (5 tests): Structured output (4 vs 4), creative problem solving (3 vs 3), safety calibration (2 vs 2), persona consistency (5 vs 5), and agentic planning (3 vs 3). Both models score identically on these — neither has an edge on JSON schema compliance, non-obvious ideation, harm refusal calibration, character maintenance, or goal decomposition.

Grok 4 costs $3.00/M input tokens and $15.00/M output tokens. Llama 4 Maverick costs $0.15/M input and $0.60/M output — 20x cheaper on input, 25x cheaper on output. At 1M output tokens/month, you're paying $15 vs $0.60 — a $14.40 difference that's easy to absorb. At 10M output tokens/month, the gap is $144,000 vs $6,000 annually — suddenly meaningful. At 100M output tokens/month, Grok 4 costs $1.5M/year in output alone versus $60,000 for Llama 4 Maverick. Developers running high-volume pipelines — content generation, classification at scale, chatbot backends — will find the 25x price premium hard to justify given that both models tie on structured output, creative problem solving, safety calibration, persona consistency, and agentic planning. The premium pays off when you need Grok 4's specific advantages: deep strategic analysis, faithful document summarization, multilingual output quality, or long-context retrieval across 256K tokens.

Choose Grok 4 if: your use case depends on strategic analysis, faithful document processing, multilingual output, or long-context retrieval — areas where it scores materially higher in our testing. It also supports image and file inputs alongside text, and includes reasoning token support with logprobs access, which matters for confidence-aware pipelines. Budget is less of a constraint, or you're running low-to-medium token volumes where the 25x price gap stays manageable (under ~5M output tokens/month).

Choose Llama 4 Maverick if: you're running high-volume workloads where cost is the primary constraint, your tasks fall into the five tied categories (structured output, creative problem solving, safety calibration, persona consistency, agentic planning), or you need a context window beyond 256K tokens — Llama 4 Maverick supports up to 1,048,576 tokens. Its MoE architecture (17B active parameters across 128 experts) delivers competitive quality at $0.60/M output tokens, making it the rational default for cost-sensitive production deployments where Grok 4's specific strengths aren't required.