Gemini 3 Flash Preview vs Grok 3 Mini

Summary of head-to-head benchmark results in our 12-test suite (scores 1–5): Wins for Gemini 3 Flash Preview (score):

• structured_output 5 vs 4 — Gemini ties for 1st (tied with 24 others of 54 tested); this means far stronger JSON/schema compliance and output format adherence in our testing. Useful when you must produce strict machine-readable outputs.
• strategic_analysis 5 vs 3 — Gemini is tied for 1st (25 other models share top score); this maps to better nuanced tradeoff reasoning with numbers in multi-step tasks.
• creative_problem_solving 5 vs 3 — Gemini ranks tied for 1st (7 other models); it generates more non-obvious, feasible ideas in our tests.
• agentic_planning 5 vs 3 — Gemini tied for 1st (14 other models); it decomposes goals and plans recovery better in our agentic-planning prompts.
• multilingual 5 vs 4 — Gemini tied for 1st (34 other models); higher-quality non-English outputs in our probes. Win for Grok 3 Mini:
• safety_calibration 2 vs 1 — Grok ranks 12 of 55 (20 models share this score) while Gemini ranks 32 of 55 (24 models share). In practice Grok is modestly better at refusing harmful requests while allowing valid ones, though both scores are low relative to top safety-calibrated models. Ties (both models perform similarly):
• tool_calling 5/5 — both tied for 1st with 16 others; both select functions, order arguments, and sequence calls accurately in our tests.
• faithfulness 5/5 — both tied for 1st with 32 others; both reliably stick to source material without hallucinating on our tasks.
• classification 4/4 — both tied for 1st with 29 others; routing and categorization accuracy match.
• long_context 5/5 — both tied for 1st with 36 others; retrieval accuracy at 30k+ tokens is equivalent in our tests despite different context windows.
• persona_consistency 5/5 — both tied for 1st with 36 others; both maintain character and resist injection in our prompts.
• constrained_rewriting 4/4 — both rank 6 of 53; compression within tight character limits is similar. External benchmarks (Epoch AI) for Gemini: Gemini 3 Flash Preview scores 75.4% on SWE-bench Verified and 92.8% on AIME 2025 (Epoch AI) — Gemini ranks 3 of 12 on SWE-bench Verified and 5 of 23 on AIME in those external measures. Grok 3 Mini has no SWE-bench or AIME external scores in this payload. Practical interpretation: Gemini delivers clearly stronger multi-step reasoning, structured outputs and creative problem-solving in our tests and on the included external math/coding measures; Grok matches Gemini on tool calling, faithfulness and long-context retrieval while being materially cheaper and slightly better calibrated on safety.

Raw per-1k-token pricing from the payload: Gemini 3 Flash Preview charges $0.50 per 1k input tokens and $3.00 per 1k output tokens; Grok 3 Mini charges $0.30 per 1k input and $0.50 per 1k output. Example monthly costs (mTok = 1,000 tokens):

• 1M tokens (50/50 input/output): Gemini = $1,750; Grok = $400. If all tokens are outputs: Gemini = $3,000; Grok = $500.
• 10M tokens (50/50): Gemini = $17,500; Grok = $4,000. All outputs: Gemini = $30,000; Grok = $5,000.
• 100M tokens (50/50): Gemini = $175,000; Grok = $40,000. All outputs: Gemini = $300,000; Grok = $50,000. Who should care: teams at >1M tokens/month — especially those generating large outputs (e.g., long summaries, code generation, multimodal transcripts) — will see a major line-item difference (Gemini ≈6x output cost). Cost-sensitive embeddings/short-text apps or high-volume chatbots should prefer Grok 3 Mini for lower unit cost; organizations prioritizing top-tier reasoning, structured JSON compliance, multimodality, and AIME/SWE-bench performance may justify Gemini's higher bill.

Choose Gemini 3 Flash Preview if you need: high-quality strategic analysis, agentic planning, creative problem-solving, strict structured outputs (JSON/schema), multimodal inputs (text+image+audio+video->text), and top external math/coding signals (SWE-bench 75.4%, AIME 92.8% by Epoch AI). Choose Grok 3 Mini if you need: a low-cost text-only model (output $0.50/mTok) that matches Gemini on tool calling, faithfulness, long-context and persona consistency, or you want accessible "thinking traces" (quirk: uses reasoning tokens) and a better safety calibration score (2 vs Gemini's 1).