DeepSeek V3.2 vs GPT-5.1

Across our 12-test suite DeepSeek V3.2 wins in structured_output (DeepSeek 5 vs GPT-5.1 4) and agentic_planning (DeepSeek 5 vs GPT-5.1 4). GPT-5.1 wins tool_calling (4 vs DeepSeek 3) and classification (4 vs DeepSeek 3). The remaining eight tests are ties: strategic_analysis (both 5), constrained_rewriting (both 4), creative_problem_solving (both 4), faithfulness (both 5), long_context (both 5), safety_calibration (both 2), persona_consistency (both 5), and multilingual (both 5). Practical implications: structured_output (JSON/schema compliance) favors DeepSeek — it is tied for 1st on structured_output in our rankings (tied with 24 others), while GPT-5.1 is midpack (rank 26 of 54). For tool-based flows — selecting functions, arguments and sequencing — GPT-5.1's tool_calling score of 4 places it at rank 18 of 54 versus DeepSeek's rank 47, meaning GPT-5.1 is measurably better for reliable function-invocation workflows. For routing and categorization, GPT-5.1's classification score ties for 1st (rank 1 of 53) while DeepSeek is rank 31, so expect fewer misroutes with GPT-5.1. Both models are top-tier on long-context, persona_consistency and faithfulness in our tests (tied for 1st in several of those measures), but both score low on safety_calibration (2). On external benchmarks, GPT-5.1 scores 68 on SWE-bench Verified and 88.6 on AIME 2025 (both from Epoch AI), which supplements our internal results; DeepSeek has no external SWE-bench/AIME scores in the payload.

Raw unit prices: DeepSeek V3.2 charges $0.26 input / $0.38 output per mTok; GPT-5.1 charges $1.25 input / $10.00 output per mTok. Assuming a 50/50 split of input vs output tokens, that equals roughly $320 per 1M total tokens on DeepSeek vs $5,625 per 1M on GPT-5.1. At 10M tokens/month that's ~$3,200 vs ~$56,250; at 100M it's ~$32,000 vs ~$562,500. The gap matters for production workloads and high-volume APIs—cost-sensitive teams and startups should favor DeepSeek; enterprise products that need GPT-5.1's tool_calling/classification strengths must budget for an order-of-magnitude higher spend.

Choose DeepSeek V3.2 if you need: strict schema/JSON outputs, strong agentic planning, cost-efficient production at scale (input $0.26 / output $0.38 per mTok), or large-context text workflows with lower spend (context window 163,840). Choose GPT-5.1 if you need: better tool_calling and classification (tool_calling 4 vs 3, classification 4 vs 3), multimodal inputs (text+image+file->text), or if third‑party benchmarks (SWE-bench 68, AIME 2025 88.6 — Epoch AI) are important and you can absorb much higher costs ($1.25/$10 per mTok).