Gemma 4 26B A4B vs o3

Summary of our 12-test head-to-head (scores are our 1–5 internal ratings unless otherwise noted):

• Agentic planning: Gemma 4 = 4, o3 = 5 — o3 wins; in our rankings o3 is tied for 1st (rank 1 of 54, tied with 14 others), Gemma ranks 16 of 54. This means o3 is stronger at goal decomposition and recovery for multi-step agents.
• Structured output: Gemma 4 = 5, o3 = 5 — tie; both are tied for 1st (tied with 24 others) for JSON/schema compliance, so both are reliable for strict format outputs.
• Faithfulness: Gemma 4 = 5, o3 = 5 — tie; both tied for 1st (tied with 32 others), indicating low hallucination risk in our tests.
• Classification: Gemma 4 = 4, o3 = 3 — Gemma wins and is tied for 1st of 53 (29 others share score); expect better routing/categorization from Gemma in our evaluation.
• Long context: Gemma 4 = 5, o3 = 4 — Gemma wins and is tied for 1st in long-context retrieval (tied with 36 others), while o3 ranks lower (rank 38 of 55). Use Gemma where 30k+ token context fidelity matters.
• Multilingual & Persona consistency: both 5 — ties; both models rank tied for 1st on multilingual and persona benchmarks, so non-English or role-based tasks are comparable.
• Constrained rewriting: Gemma 4 = 3, o3 = 4 — o3 wins; o3 ranks 6 of 53 on constrained rewriting (stronger at tight-character compression), Gemma sits mid-pack (rank 31 of 53).
• Creative problem solving: both 4 — tie; both rank similarly (rank 9 of 54), providing comparable idea-generation quality in our tests.
• Strategic analysis: both 5 — tie; both tied for 1st for nuanced numeric tradeoffs in our suite.
• Tool calling: both 5 — tie; both tied for 1st (tied with 16 others), so both select functions and arguments accurately in our evaluations.
• Safety calibration: both 1 — tie; both rank equivalently low on refusal/allow balance in our tests. External benchmarks (attributed): o3 scores 62.3% on SWE-bench Verified (Epoch AI), 97.8% on MATH Level 5 (Epoch AI), and 83.9% on AIME 2025 (Epoch AI). Gemma has no external Epoch AI scores in the payload. The external math/coding numbers show o3's strength on formal math and competition-style problems, consistent with its wins on agentic planning and constrained rewriting.

Per the payload, Gemma 4 26B A4B charges $0.08 per mTok input and $0.35 per mTok output; o3 charges $2 input and $8 output. Interpreting mTok as 1,000 tokens, per-million-token costs are: Gemma input $80 / output $350; o3 input $2,000 / output $8,000. Using a 50/50 input-output split as a concrete example: 1M tokens/month costs about $215 on Gemma vs $5,000 on o3; 10M costs ~$2,150 vs $50,000; 100M costs ~$21,500 vs $500,000. The gap matters for high-volume products (SaaS, search, moderation, analytics) — at 10M+ tokens/month, Gemma saves tens of thousands monthly. Small teams or one-off experiments may absorb o3's higher cost for its edge in certain technical tasks, but cost-sensitive deployments should favor Gemma.

Choose Gemma 4 26B A4B if: you need massive context (30k+ tokens), strict structured output, multilingual or classification reliability, and dramatically lower cost for production volumes (e.g., ~$215/1M tokens at a 50/50 split). Choose o3 if: you require stronger agentic planning, constrained rewriting (tight character budgets), or elite math/coding performance backed by external tests (o3 scores 97.8% on MATH Level 5 per Epoch AI), and you can absorb much higher per-token costs.