DeepSeek V3.1 vs GPT-5.4 Mini

All benchmark claims below are from our 12-test suite. Summary: GPT-5.4 Mini wins 6 tests, DeepSeek V3.1 wins 1, and 5 are ties. Detailed walk-through: - Faithfulness: both score 5/5 (tie). Both are tied for 1st — "tied for 1st with 32 other models out of 55 tested" — so both are among the most faithful in our pool (faithfulness = sticks to source material). - Structured output: both 5/5 (tie) and both "tied for 1st with 24 other models out of 54" — strong JSON/schema adherence for either model. - Long context: both 5/5 (tie), each "tied for 1st with 36 other models out of 55" — reliable at 30K+ token retrieval tasks. - Persona consistency & agentic planning: ties (persona_consistency 5/5 tied for 1st; agentic_planning 4/5, both rank 16 of 54). Good for multi-turn, role-driven flows. - Classification: GPT-5.4 Mini 4 vs DeepSeek 3 — GPT wins; GPT-5.4 Mini is "tied for 1st with 29 other models out of 53" on classification, which matters for routing, tagging, and accurate categorization. - Tool calling: GPT-5.4 Mini 4 vs DeepSeek 3 — GPT wins and ranks 18 of 54, indicating better function selection, argument accuracy and sequencing in our tests. - Constrained rewriting: GPT-5.4 Mini 4 vs DeepSeek 3 — GPT ranks 6 of 53 on compression within hard limits; DeepSeek sits mid-pack. This affects UIs, SMS-length summarization, and strict character-limited outputs. - Strategic analysis: GPT-5.4 Mini 5 vs DeepSeek 4 — GPT is stronger at nuanced tradeoff reasoning (GPT tied for 1st with 25 others). - Multilingual: GPT-5.4 Mini 5 vs DeepSeek 4 — GPT is tied for 1st with 34 others out of 55, delivering higher parity across non-English languages. - Creative problem solving: DeepSeek V3.1 5 vs GPT-5.4 Mini 4 — DeepSeek wins and is tied for 1st with 7 other models, producing more non-obvious, feasible ideas in our tests. - Safety calibration: GPT-5.4 Mini 2 vs DeepSeek V3.1 1 — GPT has a modest advantage (rank 12 of 55 vs DeepSeek rank 32), meaning GPT more often refused harmful prompts while permitting legitimate ones in our suite. Practical meaning: choose GPT-5.4 Mini when you need higher accuracy for classification, robust tool orchestration, constrained-length rewriting, multilingual parity, and strategic reasoning. Choose DeepSeek V3.1 if you prioritize creative idea generation, matched faithfulness/long-context results, and dramatically lower per-token cost.

DeepSeek V3.1: input $0.15/mTok, output $0.75/mTok. GPT-5.4 Mini: input $0.75/mTok, output $4.50/mTok. Per 1,000,000 tokens (1000 mTok): input-only costs = DeepSeek $150 vs GPT-5.4 Mini $750; output-only = DeepSeek $750 vs GPT-5.4 Mini $4,500. For a 50/50 input/output split per 1M tokens: DeepSeek ≈ $450, GPT-5.4 Mini ≈ $2,625. Scale those linearly: at 10M tokens/month: DeepSeek ≈ $4,500 vs GPT-5.4 Mini ≈ $26,250 (50/50). At 100M tokens/month: DeepSeek ≈ $45,000 vs GPT-5.4 Mini ≈ $262,500 (50/50). Who should care: high-throughput production apps, startups, and anyone with large-scale cost budgets should prefer DeepSeek V3.1 for cost savings; teams that need the specific quality advantages GPT-5.4 Mini shows on classification, tool orchestration, constrained rewriting and multilingual workloads may justify the higher spend.

Choose DeepSeek V3.1 if cost-per-token matters and your priority is creative problem generation, long-context retrieval, schema compliance and tight budgets: it delivers top-tier faithfulness, long-context and structured-output at $0.75 output/mTok. Choose GPT-5.4 Mini if you need stronger classification, tool calling, constrained rewriting, multilingual parity and strategic analysis despite higher cost: it wins 6 of 12 benchmarks and justifies spend for workflows that depend on those strengths.