DeepSeek V3.2 vs GPT-4o

All internal scores below are “in our testing.” Win/loss summary: DeepSeek V3.2 wins 9 of 12 tests, GPT-4o wins 2, and 1 ties. Test-by-test: • structured_output — DeepSeek 5 vs GPT-4o 4: DeepSeek ties for 1st ("tied for 1st with 24 other models out of 54 tested"); means better JSON/schema compliance in our tests. • long_context — DeepSeek 5 vs GPT-4o 4: DeepSeek ties for 1st ("tied for 1st with 36 other models out of 55 tested"); better retrieval/consistency at 30K+ tokens. • persona_consistency — tie 5 vs 5: both tied for 1st in persona resistance. • faithfulness — DeepSeek 5 vs GPT-4o 4: DeepSeek ties for 1st ("tied for 1st with 32 other models out of 55 tested"), indicating fewer source hallucinations on our suite. • agentic_planning — DeepSeek 5 vs GPT-4o 4: DeepSeek tied for 1st ("tied for 1st with 14 other models out of 54 tested"), showing stronger goal decomposition and recovery. • multilingual — DeepSeek 5 vs GPT-4o 4: DeepSeek tied for 1st ("tied for 1st with 34 other models out of 55 tested"). • strategic_analysis — DeepSeek 5 vs GPT-4o 2: DeepSeek tied for 1st ("tied for 1st with 25 other models out of 54 tested"), meaning stronger nuanced tradeoff reasoning in our tests. • constrained_rewriting — DeepSeek 4 vs GPT-4o 3: DeepSeek ranks 6 of 53, better for tight-character compression. • creative_problem_solving — DeepSeek 4 vs GPT-4o 3: DeepSeek ranks 9 of 54, delivering more non-obvious feasible ideas in our suite. • safety_calibration — DeepSeek 2 vs GPT-4o 1: DeepSeek ranks 12 of 55 vs GPT-4o 32 of 55, so DeepSeek better balances refusal/allow decisions on risky prompts in our testing. • tool_calling — DeepSeek 3 vs GPT-4o 4: GPT-4o wins and ranks 18 of 54 vs DeepSeek rank 47 of 54, so GPT-4o selects functions/args and sequencing more reliably in our tool-calling tests. • classification — DeepSeek 3 vs GPT-4o 4: GPT-4o ties for 1st ("tied for 1st with 29 other models out of 53 tested"), making it stronger at routing/labeling tasks in our suite. External benchmarks (Epoch AI): GPT-4o also reports 31% on SWE-bench Verified, 53.3% on MATH Level 5, and 6.4% on AIME 2025 (these are Epoch AI scores and shown for supplementary context). Overall interpretation: DeepSeek delivers stronger structured outputs, long-context handling, faithfulness, agentic planning and multilingual performance in our tests; GPT-4o is better at tool_calling and classification, and offers multimodal inputs per the payload (text+image+file→text).

Costs from the payload: DeepSeek V3.2 input $0.26 / output $0.38 per mTok; GPT-4o input $2.50 / output $10.00 per mTok. Using a common 50/50 input–output split as an example: • 1M tokens/month → DeepSeek ≈ $320 (500k input = $130; 500k output = $190). GPT-4o ≈ $6,250 (500k input = $1,250; 500k output = $5,000). • 10M tokens/month → DeepSeek ≈ $3,200; GPT-4o ≈ $62,500. • 100M tokens/month → DeepSeek ≈ $32,000; GPT-4o ≈ $625,000. Who should care: high-volume chat, indexing, or analytics products will see enormous savings with DeepSeek; teams that need GPT-4o’s specific wins (tool_calling and classification quality) should budget accordingly. These calculations use the per-mTok prices from the payload and assume mTok = 1k-token billing units; adjust if your usage mix (input vs output) differs.

Choose DeepSeek V3.2 if you need: long-context retrieval and consistency (163,840 token context), strict JSON/schema outputs (5/5 in our tests), faithfulness, agentic planning, multilingual quality — and much lower costs (input $0.26 / output $0.38 per mTok). Choose GPT-4o if you need: stronger tool_calling and classification accuracy in our tests, multimodal inputs (text+image+file→text), and you can accept substantially higher costs (input $2.50 / output $10.00 per mTok). If budget and high-volume throughput matter, DeepSeek is the pragmatic default; if a specific workflow hinges on function selection or classification quality and budget is secondary, evaluate GPT-4o for that slot.