GPT-5 Nano vs Llama 4 Maverick

Across our 12-test suite GPT-5 Nano wins 7 benchmarks, Llama 4 Maverick wins 1, and 4 tests tie. Key head-to-heads: - Structured output: GPT-5 Nano scored 5 and is tied for 1st of 54 models (tied with 24 others); Llama scored 4 (rank 26 of 54). This means Nano is more reliable for strict JSON/schema outputs. - Long context: Nano scored 5 and is tied for 1st of 55 (tied with 36 others); Maverick scored 4 (rank 38 of 55). In practice Nano handled retrieval and continuity across 30K+ token scenarios better in our tests despite Maverick's larger raw window. - Multilingual: Nano 5 (tied for 1st of 55) vs Maverick 4 (rank 36 of 55) — Nano gives more equivalent non-English quality. - Tool calling: Nano 4 (rank 18 of 54) won this head-to-head; Maverick's tool calling run hit a 429 rate limit on OpenRouter during testing. - Strategic analysis & agentic planning: Nano scored 4 vs Maverick's 2–3, placing Nano higher for nuanced tradeoff reasoning and decomposition (Nano rank 27 for strategic analysis; Maverick rank 44). - Safety calibration: Nano 4 (rank 6 of 55) vs Maverick 2 (rank 12 of 55) — Nano refused harmful prompts more reliably in our tests. - Persona consistency: Maverick wins 5 vs Nano 4 and is tied for 1st of 53 models (tied with 36 others) — Maverick better preserves character and resists injection. - Ties: constrained rewriting, creative problem solving, faithfulness, and classification were effectively even in our suite. External math benchmarks: beyond our internal tests, GPT-5 Nano scores 95.2% on MATH Level 5 and 81.1% on AIME 2025 (Epoch AI), which supplements its high mathematical performance; Maverick has no external scores in the payload. Rankings indicate Nano often ranks in the top quartile for structured output, long context, multilingual, and safety — practical wins for production pipelines that need reliability and lower cost.

Per the payload, GPT-5 Nano charges $0.05 input / $0.40 output per mTok; Llama 4 Maverick charges $0.15 input / $0.60 output per mTok. Assuming 1 mTok = 1,000 tokens and a 50/50 input/output split: for 1M tokens (1,000 mToks) Nano ≈ $225/month (500*$0.05 + 500*$0.40) vs Maverick ≈ $375/month (500*$0.15 + 500*$0.60) — a $150/month gap. At 10M tokens (10,000 mToks) Nano ≈ $2,250 vs Maverick ≈ $3,750 (gap $1,500). At 100M tokens Nano ≈ $22,500 vs Maverick ≈ $37,500 (gap $15,000). If your usage is high-volume (millions of tokens/month) the cheaper per-mTok rates of GPT-5 Nano materially reduce operating cost; smaller-scale, persona-focused projects may justify Maverick's higher price for its strengths.

Choose GPT-5 Nano if you need: - Reliable structured outputs/JSON schema adherence (5/tied for 1st). - Strong long-context performance (5/tied for 1st) and multilingual parity (5/tied for 1st). - Lower operating cost at scale ($0.05 input / $0.40 output per mTok). Choose Llama 4 Maverick if you need: - The best persona consistency (Maverick scores 5 and is tied for 1st) for character-driven assistants or agents. - Extra raw context headroom (Maverick has a 1,048,576 token context_window and 16,384 max output tokens in the payload) and you can tolerate higher per-token cost.