Gemma 4 31B vs o3

Summary of our 12-test suite comparisons (scores are our 1–5 internal scale unless noted): - Classification: Gemma 4 (4) vs o3 (3). Gemma wins; Gemma is tied for 1st with 29 others in our rankings. This matters for routing, intent detection, and labeling accuracy in production pipelines. - Safety calibration: Gemma 2 vs o3 1 — Gemma refuses harmful prompts more reliably in our testing (Gemma rank 12 of 55; o3 rank 32 of 55). - Structured output: both 5 — tied for 1st with 24 others; both enforce JSON/schema formats well. - Strategic analysis: both 5 — tied for 1st; both handle nuanced tradeoffs and numeric reasoning equally in our tests. - Tool calling and agentic planning: both score 5 and tie for 1st; both select functions, arguments, and decompose goals effectively in our agent tests. - Faithfulness, persona consistency, multilingual: both score 5 and tie for 1st, indicating low hallucination, stable persona, and strong non-English output in our suite. - Creative problem solving and constrained rewriting: both score 4 (tie). - Long context: both score 4 (tie; rank 38 of ~55) though Gemma has a larger context window in the payload (262,144 vs 200,000 tokens). - External benchmarks (Epoch AI): o3 posts external results included in the payload — MATH Level 5 97.8% (ranked 2 of 14, shared), SWE-bench Verified 62.3% (rank 9 of 12), AIME 2025 83.9% (rank 12 of 23). Gemma has no external benchmark scores in the payload to compare. In short: on our internal multi-task suite Gemma wins classification and safety; most other internal categories are ties. Where o3 stands out is third-party math achievement (Epoch AI), which supports choosing o3 for math-heavy or formal STEM tasks.

Per the payload rates (per 1k tokens): Gemma 4 31B input $0.13 / output $0.38; o3 input $2 / output $8. Using a 50/50 input/output token split as an example: - 1M tokens (500k in / 500k out): Gemma ≈ $255; o3 ≈ $5,000. - 10M tokens: Gemma ≈ $2,550; o3 ≈ $50,000. - 100M tokens: Gemma ≈ $25,500; o3 ≈ $500,000. The absolute gap grows linearly: at 10M+ tokens the difference is tens of thousands monthly. Cost-sensitive deployments (high-volume APIs, SaaS with many users, or always-on agents) should prefer Gemma; teams buying specialist math/coding accuracy with third-party validation may accept o3's ~20x–200x higher bill depending on IO mix.

Choose Gemma 4 31B if you need: - A cost-efficient AI for high-volume production (input $0.13 / output $0.38 per 1k). - Strong classification, better safety refusals in our testing, top-tier structured output and multilingual support. - Extremely large context needs (payload shows 262,144 tokens). Choose o3 if you need: - Verified, high-end math/technical performance as demonstrated by external scores (MATH Level 5: 97.8% on Epoch AI) and are willing to pay substantially more (input $2 / output $8 per 1k). - A provider-backed model with strong third-party math benchmarks for specialized STEM or competition-level tasks.