Gemma 4 26B A4B vs Ministral 3 3B 2512

Across our 12‑test suite, Gemma wins 8 tasks, Ministral wins 1, and 3 are ties (faithfulness, classification, safety calibration). Detailed breakdown (scores shown are from our testing, 1–5):

• Structured output: Gemma 5 vs Ministral 4 — Gemma tied for 1st (tied with 24 others out of 54), meaning it reliably follows JSON/schema constraints in production pipelines.
• Strategic analysis: Gemma 5 vs Ministral 2 — Gemma tied for 1st (25 others) so it handles nuanced tradeoffs and numeric reasoning far better for business decisions.
• Constrained rewriting: Gemma 3 vs Ministral 5 — Ministral tied for 1st (with 4 others), so it’s best when you must compress text into tight character limits.
• Creative problem solving: Gemma 4 vs Ministral 3 — Gemma ranks well (rank 9 of 54), producing more non‑obvious, feasible ideas.
• Tool calling: Gemma 5 vs Ministral 4 — Gemma tied for 1st (with 16 others), which matters where function selection, argument accuracy, and sequencing are critical.
• Faithfulness: Gemma 5 vs Ministral 5 — tie; both rank tied for 1st (32 others), so neither has an advantage on sticking to source material in our tests.
• Classification: Gemma 4 vs Ministral 4 — tie; both tied for 1st (29 others), so routing/categorization should be similar.
• Long context: Gemma 5 vs Ministral 4 — Gemma tied for 1st (36 others); combined with a 262,144 token window (vs 131,072) this yields better retrieval and coherence across 30K+ token tasks.
• Safety calibration: Gemma 1 vs Ministral 1 — tie (both rank mid/low), so expect similar refusal/permissiveness behavior in risky prompts.
• Persona consistency: Gemma 5 vs Ministral 4 — Gemma tied for 1st (36 others), useful for bots and brand voice control.
• Agentic planning: Gemma 4 vs Ministral 3 — Gemma rank 16 of 54 (26 share score); better at decomposition and failure recovery.
• Multilingual: Gemma 5 vs Ministral 4 — Gemma tied for 1st (34 others), so non‑English parity is stronger in our tests. Practical meaning: Gemma is the clear quality leader for long context, structured outputs, tool calling, multilingual and persona tasks. Ministral’s standout is constrained rewriting (compression), and it offers a much lower output price, so it’s preferable where budgets or short outputs dominate.

Gemma input = $0.08/1k tokens and output = $0.35/1k; Ministral input = $0.10/1k and output = $0.10/1k. For a 50/50 input/output mix that means: 1M tokens/month → Gemma ≈ $215, Ministral ≈ $100; 10M → Gemma ≈ $2,150, Ministral ≈ $1,000; 100M → Gemma ≈ $21,500, Ministral ≈ $10,000. If your workload is output‑heavy (e.g., long generations), Gemma’s $0.35/1k output makes it ~3.5× more expensive on output alone (priceRatio 3.5). Choose Ministral when budget at scale matters (10M+ tokens/month) or when you need a predictable, symmetric price; choose Gemma when quality on long context, structured outputs, or tool calling justifies the higher per‑token spend.

Choose Gemma 4 26B A4B if you need: high‑fidelity structured outputs, 262K token context windows, best‑in‑class tool calling (5/5), stronger strategic analysis and multilingual support — and you can absorb higher output costs ($0.35/1k). Choose Ministral 3 3B 2512 if you need: the cheapest output pricing ($0.10/1k) for high‑volume workloads, the best constrained‑rewriting performance (5/5), and a compact model with vision→text support and a 131K context window.