Gemma 4 31B vs GPT-5 Nano

Head-to-head by test (scores are our 1–5 scale):

• Tool calling: Gemma 4 31B 5 vs GPT-5 Nano 4 — Gemma ties for 1st (tied with 16 others of 54), meaning it's among the best at function selection, argument accuracy, and sequencing in our tests. Expect fewer tool-selection errors with Gemma.
• Strategic analysis: Gemma 5 vs GPT-5 Nano 4 — Gemma is tied for 1st (with 25 others of 54), showing better nuanced tradeoff reasoning and numeric tradeoffs in our suite. Use Gemma for complex decision support.
• Classification: Gemma 4 vs GPT-5 Nano 3 — Gemma is tied for 1st (tied with 29 others of 53); GPT-5 Nano ranks 31/53. Gemma is more reliable for routing and labeling tasks in our testing.
• Faithfulness: Gemma 5 vs GPT-5 Nano 4 — Gemma ties for 1st (with 32 others of 55), so it sticks closer to source material in our benchmarks. Fewer hallucinations expected with Gemma.
• Persona consistency: Gemma 5 vs GPT-5 Nano 4 — Gemma tied for 1st (with 36 others), so it better maintains role and resists injection in chat-style apps.
• Agentic planning: Gemma 5 vs GPT-5 Nano 4 — Gemma tied for 1st (with 14 others), giving stronger goal decomposition and failure recovery in our tests.
• Creative problem solving: Gemma 4 vs GPT-5 Nano 3 — Gemma ranks 9/54 (21 models share the score) versus GPT-5 Nano rank 30/54; Gemma produces more non-obvious feasible ideas in our suite.
• Constrained rewriting: Gemma 4 vs GPT-5 Nano 3 — Gemma ranks 6/53 (25 models share this score) and handles hard character/byte limits better in our testing.
• Long context: Gemma 4 vs GPT-5 Nano 5 — GPT-5 Nano ties for 1st (with 36 others of 55) and outperforms Gemma for retrieval accuracy at 30K+ tokens in our tests; GPT-5 Nano also has a larger context window (400,000 vs Gemma's 262,144).
• Safety calibration: Gemma 2 vs GPT-5 Nano 4 — GPT-5 Nano ranks 6/55 (tied with 3) while Gemma ranks 12/55; GPT-5 Nano more reliably refuses harmful requests while permitting legitimate ones in our testing.
• Structured output and Multilingual: both models score 5 and tie for 1st on structured output (tied with 24 others of 54) and multilingual (tied with 34 others of 55). Expect both to handle JSON/schema and non-English output equally well in our benchmarks. External math benchmarks: GPT-5 Nano scores 95.2% on MATH Level 5 and 81.1% on AIME 2025 (Epoch AI); these external measures indicate strong math performance for GPT-5 Nano and are reported by Epoch AI (not our internal 1–5 scores). Overall: Gemma wins 8 of 12 internal tests (tool-calling, strategy, classification, faithfulness, persona, agentic planning, creative problem solving, constrained rewriting). GPT-5 Nano wins 2 (long context, safety calibration). Two tests tie.

Per the payload, Gemma 4 31B charges $0.13 per k-token input and $0.38 per k-token output; GPT-5 Nano charges $0.05 input and $0.40 output. At 1M tokens/month (1,000 m-tokens): Gemma input-only = $130, output-only = $380, 50/50 = $255. GPT-5 Nano input-only = $50, output-only = $400, 50/50 = $225. At 10M tokens/month (10,000 m-tokens): Gemma 50/50 = $2,550 vs GPT-5 Nano 50/50 = $2,250. At 100M tokens/month (100,000 m-tokens): Gemma 50/50 = $25,500 vs GPT-5 Nano 50/50 = $22,500. If your workload is input-heavy (large prompts, analytics, indexing), GPT-5 Nano's $0.05 input price saves substantial dollars at scale. If your workload is output-heavy (long generated texts, large responses), Gemma's $0.38 output price is slightly cheaper than GPT-5 Nano's $0.40 and can save at high output volumes. The net price gap is meaningful at tens of millions of tokens; small projects (<1M tokens/month) should prioritize capability over the modest cost differences.

Choose Gemma 4 31B if: you need the best tool-calling, strategic analysis, faithful source adherence, classification, persona consistency, agentic planning, constrained rewriting, or creative idea generation — especially for apps that call functions, decompose goals, or must avoid hallucination. Choose GPT-5 Nano if: you need the longest context window and best long-context retrieval accuracy, stronger safety calibration, or the lowest input cost at scale (e.g., large prompt analytics or developer tools). If cost is the primary constraint and your workload is input-heavy, GPT-5 Nano is the cheaper choice; if capability across tool-driven workflows and fidelity matter more, Gemma is the better pick.