DeepSeek V3.1 Terminus vs GPT-5.4 Mini

Our 12-test suite split: GPT-5.4 Mini wins 6 tests, DeepSeek V3.1 Terminus wins 0, and 6 are ties. Tie wins (both models): structured_output (5/5 each; both tied for 1st), strategic_analysis (5/5 each; both tied for 1st), creative_problem_solving (4/4; both rank 9/54), long_context (5/5 each; both tied for 1st), agentic_planning (4/4; both rank 16/54), multilingual (5/5 each; both tied for 1st). GPT-5.4 Mini wins on constrained_rewriting (4 vs 3; ranks: GPT rank 6 of 53 vs DeepSeek 31 of 53) — meaning GPT handles tight compression and hard length limits noticeably better. GPT also wins tool_calling (4 vs 3; GPT rank 18/54 vs DeepSeek 47/54), indicating better function selection, argument accuracy and sequencing for agentic flows. Faithfulness is a clear GPT advantage (5 vs 3; GPT tied for 1st vs DeepSeek rank 52/55), which matters for citation-heavy or regulated outputs. Classification (4 vs 3; GPT tied for 1st vs DeepSeek rank 31/53), safety_calibration (2 vs 1; GPT rank 12/55 vs DeepSeek 32/55), and persona_consistency (5 vs 4; GPT tied for 1st vs DeepSeek rank 38/53) round out GPT’s wins. Practically: choose GPT-5.4 Mini when you need fewer hallucinations, robust tool-calling, accurate routing/classification, and stricter safety handling; choose DeepSeek for long documents, stable structured-output JSON, multilingual tasks, and when token costs are the dominant constraint.

Prices in the payload are listed per mTok. Assuming mTok = 1,000 tokens and a 50/50 split between input and output tokens: DeepSeek V3.1 Terminus (input $0.21, output $0.79 per mTok) costs $500 per 1M tokens (500 mTok input × $0.21 = $105; 500 mTok output × $0.79 = $395). GPT-5.4 Mini (input $0.75, output $4.50 per mTok) costs $2,625 per 1M tokens (500×$0.75 = $375; 500×$4.50 = $2,250). Scaling: at 10M tokens/month DeepSeek ≈ $5,000 vs GPT-5.4 Mini ≈ $26,250; at 100M tokens/month DeepSeek ≈ $50,000 vs GPT-5.4 Mini ≈ $262,500. The payload’s priceRatio is 0.1756, i.e., DeepSeek costs ~17.6% of GPT per-token (≈5.7× cheaper). High-throughput services and startups with tight budgets should care most about this gap; teams that need top-tier faithfulness, tool-calling correctness, and safety should budget for GPT-5.4 Mini.

Choose DeepSeek V3.1 Terminus if: you must process extremely large volumes on a budget (DeepSeek costs ~5.7× less per-token), need top long-context handling (5/5, tied for 1st), and rely on structured JSON outputs (5/5, tied for 1st) or multilingual parity. Choose GPT-5.4 Mini if: you need higher faithfulness (5 vs 3), better tool calling (4 vs 3), stronger classification (4 vs 3), safer refusals/allowances (safety 2 vs 1), or tighter persona consistency (5 vs 4). Examples: use DeepSeek for high-volume document retrieval, long-form synthesis, or cost-sensitive multilingual chat; use GPT-5.4 Mini for regulated content, production agent/tool pipelines, classification/routing services, and workflows where hallucination risk is unacceptable.