DeepSeek V3.1 Terminus vs GPT-5.2

Win/loss summary from our 12-test suite: GPT-5.2 wins 8 tests, DeepSeek V3.1 Terminus wins 1, and 3 tests tie. Detailed comparisons (score / rank context):

• Structured output: DeepSeek 5 (tied for 1st of 54, tied with 24 others) vs GPT-5.2 4 (rank 26). This means DeepSeek is more reliable for strict JSON/schema compliance in our tests.
• Constrained rewriting: GPT-5.2 4 (rank 6 of 53) vs DeepSeek 3 — GPT-5.2 better for tight character compression tasks.
• Creative problem solving: GPT-5.2 5 (tied for 1st) vs DeepSeek 4 (rank 9) — GPT-5.2 produces more non-obvious, feasible ideas in our testing.
• Tool calling: GPT-5.2 4 (rank 18) vs DeepSeek 3 (rank 47) — GPT-5.2 selects and sequences functions more accurately in our tool-calling tests.
• Faithfulness: GPT-5.2 5 (tied for 1st) vs DeepSeek 3 (rank 52 of 55) — GPT-5.2 sticks to source material far more consistently in our tests.
• Classification: GPT-5.2 4 (tied for 1st) vs DeepSeek 3 (rank 31) — GPT-5.2 routes/labels more accurately in our benchmarks.
• Safety calibration: GPT-5.2 5 (tied for 1st) vs DeepSeek 1 (rank 32) — GPT-5.2 reliably refuses harmful requests while permitting legitimate ones in our suite.
• Persona consistency & agentic planning: GPT-5.2 scores 5 on persona_consistency (tied for 1st) and 5 on agentic_planning (tied for 1st) vs DeepSeek 4 and 4 — GPT-5.2 better maintains character and decomposes goals in our tests.
• Ties: strategic_analysis (both 5, tied for 1st with many models), long_context (both 5, tied for 1st), multilingual (both 5, tied for 1st) — both models perform at the top tier on nuanced reasoning, retrieval at 30K+ tokens, and non-English output in our tests. External benchmarks (attributed): GPT-5.2 scores 73.8% on SWE-bench Verified and 96.1% on AIME 2025 according to Epoch AI — these third-party results support GPT-5.2’s coding/problem-solving and math performance. DeepSeek has no external SWE/AIME scores in the payload. Overall, GPT-5.2 dominates safety, faithfulness, tool use, and classification in our testing; DeepSeek’s standout is structured, schema-compliant output plus a much lower price.

Per-million-token rates in the payload: DeepSeek V3.1 Terminus charges $0.21 input + $0.79 output = $1.00 per 1M tokens (input+output). GPT-5.2 charges $1.75 input + $14.00 output = $15.75 per 1M tokens (input+output). At 1M tokens/month that’s $1.00 vs $15.75; at 10M it’s $10 vs $157.50; at 100M it’s $100 vs $1,575. The payload’s priceRatio (0.0564) flags DeepSeek as roughly a single-digit-percent cost of GPT-5.2. Teams running millions of tokens monthly (SaaS providers, large inference pipelines, analytics backends) should care strongly about this gap; exploratory, safety-critical, or tool-driven products will justify GPT-5.2’s higher cost in return for higher benchmark performance.

Choose DeepSeek V3.1 Terminus if you need inexpensive, high-throughput schema/JSON generation and want to minimize inference cost (it wins structured_output and costs $1.00 per 1M input+output tokens). Choose GPT-5.2 if you need a safer, more faithful model for agentic workflows, tool calling, classification, and creative problem solving (it wins 8 of 12 benchmarks and scores 73.8% on SWE-bench Verified and 96.1% on AIME 2025 per Epoch AI). If budget limits are strict and outputs are tightly structured, pick DeepSeek; if correctness, safety, and tool/agent performance matter, pick GPT-5.2 despite the higher cost.