Gemini 3.1 Flash Lite Preview vs GPT-5.4

We compared both models across our 12-test suite (scores 1–5). Results in our testing: GPT-5.4 wins 2 tests, Gemini wins 0, and 10 tests tie. Detailed walk-through: 1) Long context — GPT-5.4: 5 vs Gemini: 4. GPT-5.4 ranks tied for 1st (tied with 36 others of 55); Gemini ranks 38 of 55. This implies GPT-5.4 is measurably stronger for retrieval and reasoning over 30K+ token contexts. 2) Agentic planning — GPT-5.4: 5 vs Gemini: 4. GPT-5.4 ranks tied for 1st (14 other models), while Gemini ranks 16 of 54; expect better goal decomposition and recovery with GPT-5.4. 3) Structured output — both 5; both tied for 1st (Gemini tied with 24 others). Both models handle JSON/schema compliance at top-tier levels in our tests. 4) Strategic analysis — both 5 and tied for 1st; both are strong at nuanced tradeoff reasoning. 5) Constrained rewriting — both 4, rank 6 of 53; both perform similarly compressing to tight limits. 6) Creative problem solving — both 4, rank 9 of 54; both produce feasible, non-obvious ideas at comparable quality. 7) Tool calling — both 4, rank 18 of 54; expect similar function-selection and argument accuracy. 8) Faithfulness — both 5 and tied for 1st; both resist hallucination in our tests. 9) Classification — both 3 (rank 31 of 53); neither excels on routing/class labeling compared with top classifiers. 10) Safety calibration — both 5 and tied for 1st; both reliably refuse harmful requests while permitting legitimate ones. 11) Persona consistency — both 5 and tied for 1st; both maintain character and resist prompt injection. 12) Multilingual — both 5 and tied for 1st; both produce equivalent non-English quality in our tests. External benchmarks (supplementary): GPT-5.4 scores 76.9% on SWE-bench Verified (Epoch AI) — rank 2 of 12 — and 95.3% on AIME 2025 (Epoch AI) — rank 3 of 23. Gemini has no external SWE/AIME scores in the payload. In short: across our internal suite the two models mostly tie; GPT-5.4 pulls ahead where long-context and agentic planning matter and shows strong external math/coding signals per Epoch AI.

Raw per-million-token prices from the payload: Gemini 3.1 Flash Lite Preview charges $0.25 (input) / $1.50 (output) per 1,000,000 tokens; GPT-5.4 charges $2.50 (input) / $15.00 (output). If your usage is a 50/50 split of input/output tokens, cost per 1,000,000 total tokens is $0.875 for Gemini (0.5M0.25 + 0.5M1.5) vs $8.75 for GPT-5.4 (0.5M2.5 + 0.5M15). Scaling that: at 1M tokens/month the bill is $0.88 vs $8.75; at 10M it’s $8.75 vs $87.50; at 100M it’s $87.50 vs $875.00. The 10x per-token price gap (priceRatio = 0.1) matters for any high-volume product (chat fleets, automated document pipelines, embedding-heavy apps). Teams building low-volume prototypes or those who need the specific long-context/agentic capabilities may accept GPT-5.4’s premium; everyone else should evaluate cost first, as monthly savings quickly compound into hundreds to thousands of dollars.

Choose Gemini 3.1 Flash Lite Preview if you need a low-cost, high-throughput model with broad multimodal ingestion (text, image, file, audio, video->text), parity on 10 of 12 internal tests, and dramatically lower bills at scale (about 10% of GPT-5.4’s per-token cost). Choose GPT-5.4 if your priority is the best long-context retrieval (score 5 vs 4) and agentic planning (5 vs 4), or if external benchmarks matter (SWE-bench 76.9%, AIME 95.3% by Epoch AI) and you can absorb the 10x token price premium.