GPT-4.1 vs Llama 4 Maverick

Summary of head-to-head results in our 12-test suite: GPT-4.1 wins strategic analysis (5 vs 2), constrained rewriting (5 vs 3), tool calling (5 vs — B hit a tool calling rate-limit), faithfulness (5 vs 4), classification (4 vs 3), long context (5 vs 4), agentic planning (4 vs 3), and multilingual (5 vs 4). Llama 4 Maverick wins safety calibration (2 vs GPT-4.1's 1). The two tie on structured output (4/4), creative problem solving (3/3), and persona consistency (5/5). Context and rankings: GPT-4.1’s tool calling is tied for 1st with 16 others out of 54 tested; long context and faithfulness are tied for 1st in their pools (long context tied with 36 of 55; faithfulness tied with 32 of 55), indicating reliable retrieval and low hallucination risk in our tests. GPT-4.1’s strategic analysis and constrained rewriting are also top-ranked (strategic analysis tied for 1st with 25 of 54; constrained rewriting tied for 1st with 4 of 53), which matters for numeric tradeoffs and strict-length rewrites. Llama 4 Maverick scores higher on safety calibration (rank 12 of 55 vs GPT-4.1 rank 32 of 55), so it more frequently refuses harmful prompts in our tests. External benchmarks (Epoch AI): GPT-4.1 scores 48.5% on SWE-bench Verified, 83% on MATH Level 5, and 38.3% on AIME 2025 — we cite those as supplementary, third-party signals (Epoch AI) and did not combine them with our 1–5 internal scores. Practical implication: GPT-4.1 gives stronger end-to-end behavior for tool-based workflows, long documents, and tasks needing faithful outputs; Llama 4 Maverick offers much lower cost and modestly better safety calibration per our tests.

Per the payload, GPT-4.1 costs $2 input / $8 output per mTOK; Llama 4 Maverick costs $0.15 / $0.60 per mTOK. Using a 50/50 input-output token split: 1M tokens = 500 mTOK input + 500 mTOK output. GPT-4.1: (500*$2)+(500*$8) = $1,000 + $4,000 = $5,000 per 1M tokens. Llama 4 Maverick: (500*$0.15)+(500*$0.60) = $75 + $300 = $375 per 1M tokens. At 10M tokens/month: GPT-4.1 ≈ $50,000 vs Llama ≈ $3,750. At 100M tokens/month: GPT-4.1 ≈ $500,000 vs Llama ≈ $37,500. The price ratio in the payload is 13.333x; teams with large volume (10M+ tokens/month), consumer apps, or tight margins should prefer Llama 4 Maverick. Organizations prioritizing fewer failures on chaining, tool use, long-context tasks, or classification may find GPT-4.1’s higher cost justified for reduced engineering overhead.

Choose GPT-4.1 if you need best-in-class tool calling, reliable long-context retrieval, high faithfulness, or top classification/strategic-analysis performance and can absorb higher costs (input $2/output $8 per mTOK). Choose Llama 4 Maverick if your priority is cost-efficiency at scale (input $0.15/output $0.60 per mTOK), you need solid persona consistency, or you prefer stronger safety calibration behavior in our tests.