Gemini 3.1 Flash Lite Preview vs Gemma 4 31B

We ran 12 internal tests and compare model-by-model results below (all statements are 'in our testing'). Wins and ties: Gemma 4 31B wins tool_calling (5 vs 4), classification (4 vs 3), and agentic_planning (5 vs 4). Gemini 3.1 Flash Lite Preview wins safety_calibration (5 vs 2). The remaining eight tests are ties: structured_output (5/5), strategic_analysis (5/5), constrained_rewriting (4/4), creative_problem_solving (4/4), faithfulness (5/5), long_context (4/4), persona_consistency (5/5), multilingual (5/5). What this means in practice: - Tool calling (Gemma 4 31B: 5, Gemini 3.1: 4): Gemma 4 ranks tied for 1st on tool_calling (rank 1 of 54 tied with 16) versus Gemini’s rank 18; expect more accurate function selection, argument formatting, and sequencing from Gemma 4 in agentic pipelines. - Agentic planning (5 vs 4): Gemma 4 is tied for 1st (rank 1 of 54) vs Gemini’s rank 16, so Gemma 4 produces stronger goal decomposition and failure-recovery plans in our tests. - Classification (4 vs 3): Gemma 4 is tied for 1st (rank 1 of 53) vs Gemini at rank 31, so Gemma 4 is better at routing/categorization tasks in our testing. - Safety_calibration (5 vs 2): Gemini 3.1 is tied for 1st on safety_calibration (tied for 1st with 4 others out of 55) while Gemma 4 sits at rank 12; in our testing Gemini 3.1 better refuses harmful prompts and better permits legitimate, sensitive content. - Long context: both score 4 in our long_context test and rank similarly (rank 38 of 55), but the raw context-window difference is material: Gemini 3.1 supports 1,048,576 tokens vs Gemma 4’s 262,144 tokens (payload fields). - Structured output, faithfulness, strategic analysis: both models score 5 and tie for 1st on these tests in our evaluation, indicating parity on JSON-schema compliance, sticking to source material, and nuanced tradeoff reasoning. In short: Gemma 4 31B is the practical winner for tool-using agents, classification/routing, and agentic workflows; Gemini 3.1 Flash Lite Preview is the winner for safety-sensitive apps and extreme-context ingestion, but at roughly 4× the output cost.

Per the payload, Gemini 3.1 Flash Lite Preview charges $0.25 per mTok input and $1.50 per mTok output; Gemma 4 31B charges $0.13 per mTok input and $0.38 per mTok output. That yields 1M tokens cost (per mTok=1,000 tokens): Gemini 3.1 = $250 (1M input) + $1,500 (1M output) = $1,750 combined; Gemma 4 31B = $130 + $380 = $510 combined. At 10M tokens/month: Gemini 3.1 ≈ $17,500 vs Gemma 4 ≈ $5,100. At 100M tokens/month: Gemini 3.1 ≈ $175,000 vs Gemma 4 ≈ $51,000. The output-cost ratio (1.50 / 0.38) is ~3.95x (payload priceRatio). High-volume deployments, embedded assistants, and startups with tight margins should care about this gap; choose Gemini 3.1 only if its safety profile, extreme context window (1,048,576 vs 262,144 tokens), or other quality tradeoffs justify the 3.9× output-price premium.

Choose Gemma 4 31B if you need: - Best-in-test tool calling (5 vs 4) and agentic planning (5 vs 4) for agents, orchestration, or function-heavy assistants. - Cheaper at scale: $0.38/mTok output and $0.13/mTok input (combined cost ≈ $510 per 1M in/out tokens). Choose Gemini 3.1 Flash Lite Preview if you need: - Strong safety calibration (5 vs 2) for compliance-heavy or moderation-sensitive production. - Very large context (1,048,576 tokens) for single-document ingestion or multi-file summarization, and you accept higher cost ($1.50/mTok output, $0.25/mTok input). If budget is tight or you expect >10M tokens/month, Gemma 4 31B typically yields materially lower monthly spend; if safety calibration and maximal context matter more than cost, pick Gemini 3.1 Flash Lite Preview.