Gemini 3 Flash Preview vs GPT-5.2

Summary of our 12-test suite comparisons (internal 1–5 scores unless noted): - Gemini 3 Flash Preview wins structured_output (5 vs 4) and ranks tied for 1st among 54 models (tied with 24 others). This matters for apps that require tight JSON/schema compliance. - Gemini also wins tool_calling (5 vs 4); in our testing it’s tied for 1st (with 16 others) while GPT-5.2 ranks 18 of 54 for tool calling. That translates to more accurate function selection and argument sequencing in real agentic flows. - GPT-5.2 wins safety_calibration (5 vs 1); in our testing GPT-5.2 is tied for 1st on safety among 55 models while Gemini ranks 32 of 55. For applications that must refuse harmful prompts or apply conservative safety policies, GPT-5.2 is clearly stronger. - Many categories are ties in our testing: strategic_analysis (5/5), creative_problem_solving (5/5), faithfulness (5/5), classification (4/4), long_context (5/5), persona_consistency (5/5), agentic_planning (5/5), multilingual (5/5), and constrained_rewriting (4/4). That means for general reasoning, long-context retrieval (both tie for 1st on long_context), and multilingual outputs, both models deliver comparable top-tier results. - External benchmarks: on SWE-bench Verified (Epoch AI) Gemini scores 75.4% (rank 3 of 12) vs GPT-5.2’s 73.8% (rank 5 of 12), which aligns with Gemini’s stronger coding/tooling proxies. On AIME 2025 (Epoch AI) GPT-5.2 scores 96.1% (rank 1 of 23) vs Gemini’s 92.8% (rank 5 of 23), indicating GPT-5.2 holds an edge on high-end contest math. - Other operational differences from the payload: Gemini provides a 1,048,576-token context window vs GPT-5.2’s 400,000; GPT-5.2 supports larger max_output_tokens (128,000) than Gemini (65,536). In practice that means Gemini is preferable when you need ultra-long context and strongly structured output at low cost, while GPT-5.2 is preferable for highest safety calibration and peak math performance.

Per-token pricing (per 1,000 tokens, 'mTok'): Gemini 3 Flash Preview charges $0.50 input / $3 output; GPT-5.2 charges $1.75 input / $14 output. That makes Gemini roughly 21.4% of GPT-5.2 on the blended priceRatio in the payload. Example, for a 50/50 input/output usage mix: - 1M total tokens (500k input + 500k output): Gemini ≈ $1,750; GPT-5.2 ≈ $7,875. - 10M total tokens: Gemini ≈ $17,500; GPT-5.2 ≈ $78,750. - 100M total tokens: Gemini ≈ $175,000; GPT-5.2 ≈ $787,500. If your product is high-volume (10M+ tokens/month) the cost difference multiplies and will materially affect unit economics; startups and consumer apps with many end-users should care most. If your workload is generation-heavy (mostly output tokens), the gap widens because GPT-5.2’s $14/mTok output is an order of magnitude higher than Gemini’s $3/mTok.

Choose Gemini 3 Flash Preview if you need: - Affordable production pricing (input $0.50 / output $3 per mTok) at scale, - Best-in-class structured output and tool calling (5/5 in our tests; tied for 1st in rankings), - Very large context (1,048,576 tokens) for retrieval or multi-document workflows. Choose GPT-5.2 if you need: - Strongest safety calibration (5/5 in our tests; tied for 1st), - Top external math performance (96.1% on AIME 2025, Epoch AI, rank 1), - Higher single-response generation ceilings (128,000 max output tokens) and are willing to pay ~4.5x the per-token blended cost for those advantages.