DeepSeek V3.1 vs Gemma 4 31B

Overview: Gemma 4 31B wins on 7 benchmarks (strategic_analysis 5 vs 4, constrained_rewriting 4 vs 3, tool_calling 5 vs 3, classification 4 vs 3, safety_calibration 2 vs 1, agentic_planning 5 vs 4, multilingual 5 vs 4). DeepSeek V3.1 wins 2 (creative_problem_solving 5 vs 4, long_context 5 vs 4). Three benchmarks tie (structured_output 5/5, faithfulness 5/5, persona_consistency 5/5). Specifics and implications: - Tool calling: Gemma 5/5 and ranked tied for 1st (rank 1 of 54) vs DeepSeek 3/5 (rank 47 of 54). This means Gemma is far more reliable at selecting functions, constructing args and sequencing calls — important for agentic tool-driven workflows and function-calling UIs. - Strategic analysis: Gemma scores 5/5 (tied for 1st) vs DeepSeek 4/5 (rank 27). Expect Gemma to be stronger at nuanced tradeoff reasoning and numeric tradeoffs. - Constrained rewriting & classification: Gemma 4/5 (constrained_rewriting rank 6; classification tied for 1st) vs DeepSeek 3/5 — Gemma handles tight character limits and routing/classification tasks more accurately. - Safety calibration: Gemma 2/5 (rank 12) outperforms DeepSeek 1/5 (rank 32), indicating Gemma more consistently refuses unsafe prompts while permitting legitimate content. - Multilingual & agentic planning: Gemma 5/5 (rank 1 ties) vs DeepSeek 4/5; Gemma is the better pick for non-English quality and planning+recovery workflows. - Long-context & creative problem solving: DeepSeek 5/5 (tied for 1st on long_context and creative_problem_solving) vs Gemma 4/5. DeepSeek is clearly better when retrieval accuracy across 30K+ token contexts or generating non-obvious, feasible ideas matters. - Structured output, faithfulness, persona consistency: both score 5/5 and are tied for 1st — both are reliable for JSON schema compliance, sticking to source material, and maintaining persona. In sum: Gemma dominates developer-facing capabilities (tool calling, classification, planning) and is cheaper; DeepSeek is the specialist for very long-context retrieval and top-tier creative ideation.

Per-token pricing (per 1,000 tokens): DeepSeek V3.1 input $0.15 / output $0.75; Gemma 4 31B input $0.13 / output $0.38. Assuming a 50/50 input/output token split: for 1M tokens/month DeepSeek costs $450 vs Gemma $255 (DeepSeek +$195). At 10M tokens/month DeepSeek $4,500 vs Gemma $2,550 (+$1,950). At 100M tokens/month DeepSeek $45,000 vs Gemma $25,500 (+$19,500). The gap comes mostly from DeepSeek's higher output rate ($0.75 vs $0.38); services that generate long outputs (summaries, long-form writing, large-batch inference) or operate at high volume should prefer Gemma to save substantially. Teams focused on few high-value long-context requests or specialized creative workflows may justify DeepSeek's premium.

Choose DeepSeek V3.1 if you need: - Best-in-class long-context work (long_context 5/5, tied for 1st) such as multi-document retrieval, book-length summarization, or deep context QA; - High-quality creative ideation (creative_problem_solving 5/5) for brainstorming or strategy generation; and you can accept ~2× per-output-token cost. Choose Gemma 4 31B if you need: - A cost-efficient, general-purpose API with stronger tool calling (5/5, rank 1), strategic analysis (5/5), classification (4/5, rank 1), multilingual support (5/5), and better safety calibration; - Multimodal inputs (text+image+video->text) and very large context windows (262,144 tokens) for document- and multimodal-driven products.