DeepSeek V3.1 vs GPT-5

Summary of our 12-test head-to-head (scores are our 1–5 internal ratings unless otherwise noted). Overall wins: GPT-5 wins 7 tests, DeepSeek V3.1 wins 1, and 4 tests tie. Details (scoreA = DeepSeek, scoreB = GPT-5):

• Tool calling: DeepSeek 3 vs GPT-5 5 — GPT-5 wins and ranks tied for 1st ("tied for 1st with 16 other models out of 54 tested"); expect better function selection, argument accuracy, and sequencing with GPT-5 in agentic integrations.
• Strategic analysis: 4 vs 5 — GPT-5 wins and ranks "tied for 1st"; better at nuanced tradeoff reasoning and numeric-backed decisioning in our tests.
• Constrained rewriting: 3 vs 4 — GPT-5 wins (rank 6 of 53); GPT-5 is better at hitting hard character/space limits reliably.
• Classification: 3 vs 4 — GPT-5 wins (tied for 1st); clearer routing and labeling in our classification probes.
• Agentic planning: 4 vs 5 — GPT-5 wins (tied for 1st); better goal decomposition and failure recovery in our scenarios.
• Multilingual: 4 vs 5 — GPT-5 wins (tied for 1st); higher quality non-English output in our multilingual checks.
• Safety calibration: 1 vs 2 — GPT-5 wins but both are low; GPT-5 ranks 12 of 55 while DeepSeek ranks 32 of 55, meaning neither is exemplary at nuanced refusal/permissive behavior.
• Creative problem solving: 5 vs 4 — DeepSeek wins and is tied for 1st on creative_problem_solving ("tied for 1st with 7 other models"); expect more non-obvious feasible ideas from DeepSeek in our prompts.
• Faithfulness: 5 vs 5 — tie; both tied for 1st in faithfulness (DeepSeek display: "tied for 1st with 32 other models").
• Structured output: 5 vs 5 — tie and both tied for 1st; both handle JSON/schema compliance well.
• Long context: 5 vs 5 — tie and both tied for 1st; both preserve retrieval accuracy at 30K+ tokens in our tests.
• Persona consistency: 5 vs 5 — tie and both tied for 1st; both maintain character and resist injection in our scenarios.

External benchmarks (Epoch AI): GPT-5 scores 73.6% on SWE-bench Verified, 98.1% on MATH Level 5, and 91.4% on AIME 2025 — we reference these third-party results (Epoch AI) as supplementary evidence that GPT-5 is especially strong on advanced math and coding problem sets. DeepSeek has no external scores in the payload. In short: GPT-5 is the technical victor on most structured, planning, and classification tasks; DeepSeek shines for creative ideation while offering similar long-context and structured output behavior at a much lower price.

DeepSeek V3.1: $0.15 per mTok input and $0.75 per mTok output. GPT-5: $1.25 per mTok input and $10.00 per mTok output. For a balanced 1M input + 1M output tokens/month DeepSeek costs $900 (input $150 + output $750) vs GPT-5 $11,250 (input $1,250 + output $10,000). At 10M/10M tokens/month the totals are DeepSeek $9,000 vs GPT-5 $112,500; at 100M/100M tokens/month DeepSeek $90,000 vs GPT-5 $1,125,000. The ~12.5x higher input and ~13.3x higher output rates on GPT-5 means startups, high-volume SaaS, or embed-heavy apps should favor DeepSeek for cost control; teams that need GPT-5’s task-level advantages should budget accordingly.

Choose DeepSeek V3.1 if you need creative problem solving, very long-context interaction, schema/JSON fidelity, or you operate at high token volumes where cost matters — it matches GPT-5 on long-context, structured output, faithfulness, and persona while costing far less (example: $900 vs $11,250 at 1M in+1M out tokens/month). Choose GPT-5 if your priority is tool calling, agentic planning, strategic analysis, classification, multilingual capability, or top-tier math/coding performance (98.1% MATH Level 5, Epoch AI) and you can absorb the higher per-token cost.