GPT-5 vs Llama 4 Maverick

Overview: GPT-5 wins 10 benchmarks in our 12-test suite and ties 2 (safety calibration and persona consistency). Llama 4 Maverick does not win any benchmark outright in our testing. Per-test details and what it means:

• tool calling: GPT-5 scores 5 vs no higher score for 4 Maverick; GPT-5 is tied for 1st of 54 (tied with 16 others). This predicts more accurate function selection and argument formatting in integrated workflows.
• long context: GPT-5 5 vs 4 Maverick 4 — GPT-5 is tied for 1st of 55 (36 ties). Despite 4 Maverick’s larger raw window (1,048,576 vs GPT-5’s 400,000), GPT-5 produced better retrieval accuracy at 30K+ token tests in our suite.
• faithfulness: GPT-5 5 vs 4 Maverick 4 — GPT-5 tied for 1st of 55 (32 ties). Expect fewer hallucinations and tighter adherence to source material with GPT-5 in our tests.
• persona consistency: both tie (GPT-5 5, 4 Maverick 5) — both models maintain character well and resist injection in our evaluations (GPT-5 tied for 1st of 53; 4 Maverick also tied for 1st).
• structured output: GPT-5 5 vs 4 Maverick 4 — GPT-5 tied for 1st of 54 (24 ties). GPT-5 is stronger at schema/JSON compliance in our runs.
• strategic analysis: GPT-5 5 vs 4 Maverick 2 — GPT-5 tied for 1st of 54 (25 ties). For nuanced tradeoff reasoning with numbers, GPT-5 outperformed 4 Maverick substantially in our tests.
• constrained rewriting: GPT-5 4 vs 4 Maverick 3 — GPT-5 ranks 6 of 53; better at tight character-limited rewriting.
• creative problem solving: GPT-5 4 vs 4 Maverick 3 — GPT-5 ranks 9 of 54; better at producing specific, feasible ideas.
• classification: GPT-5 4 vs 4 Maverick 3 — GPT-5 tied for 1st of 53 (29 ties); expect higher routing/label accuracy.
• agentic planning: GPT-5 5 vs 4 Maverick 3 — GPT-5 tied for 1st of 54 (14 ties); better goal decomposition and failure recovery in our tests.
• safety calibration: tie (both 2) — rank 12 of 55 for both; both models show similar refusal/permissive balance in our suite. External benchmarks (supplementary): GPT-5 scores 73.6% on SWE-bench Verified, 98.1% on MATH Level 5, and 91.4% on AIME 2025 — these are Epoch AI results and support GPT-5’s coding and math strengths. 4 Maverick has no external scores in the payload. Operational notes: 4 Maverick hit a transient tool calling rate limit in our OpenRouter runs (429), which may affect measured tool calling performance but did not produce any wins. Rankings context: many GPT-5 top scores are ties with multiple models — 'tied for 1st' means it shares the top score rather than being a sole winner in those categories.

Costs per mTok: GPT-5 input $1.25 / output $10; Llama 4 Maverick input $0.15 / output $0.60. Assuming a 50/50 input/output token split: for 1M total tokens/month (1,000 mTok) GPT-5 costs $5,625 vs Llama 4 Maverick $375. At 10M tokens/month: GPT-5 $56,250 vs Llama 4 Maverick $3,750. At 100M tokens/month: GPT-5 $562,500 vs Llama 4 Maverick $37,500. The payload’s priceRatio is ~16.67 (GPT-5 output cost / 4 Maverick output cost). Who should care: startups and high-volume apps will see six-figure differences at scale and should prefer 4 Maverick for cost-sensitive workloads; enterprises that need the highest benchmark performance may justify GPT-5’s premium.

Choose GPT-5 if you need top performance for tool integration, long-context retrieval, math and code tasks, or mission-critical faithfulness and can absorb high inference costs (GPT-5 output $10/mTok). Choose Llama 4 Maverick if your priority is minimizing inference cost or you need a very large raw context window and you can accept lower scores on strategic analysis, tool calling, and structured output. Specifics: pick GPT-5 for production agent chains, complex multi-step reasoning, large-scale code/math workloads; pick 4 Maverick for high-volume conversational agents, cheap bulk inference, or prototyping when budget is the primary constraint.