DeepSeek V3.1 Terminus vs GPT-4.1 Nano

Summary of our 12-test suite (in our testing): wins split 4–4–4. DeepSeek V3.1 Terminus wins four tests: long_context (5 vs 4), strategic_analysis (5 vs 2), creative_problem_solving (4 vs 2), and multilingual (5 vs 4). In practical terms that means in our tests DeepSeek is better for retrieval and reasoning over 30K+ token contexts (long_context tied for 1st of 55 models, tied with 36 others) and for nuanced tradeoff reasoning (strategic_analysis tied for 1st of 54). DeepSeek’s creative_problem_solving ranks 9 of 54, and multilingual is tied for 1st of 55 — useful for multi-language products and ideation tasks. GPT-4.1 Nano wins four tests: constrained_rewriting (4 vs 3), tool_calling (4 vs 3), faithfulness (5 vs 3), and safety_calibration (2 vs 1). That maps to better compression into hard character limits (constrained_rewriting rank 6 of 53), stronger function selection and argument accuracy (tool_calling rank 18 of 54), and higher adherence to source material (faithfulness tied for 1st of 55) with fewer unsafe responses (safety_calibration rank 12 of 55). Four tests tie (structured_output 5/5, classification 3/3, persona_consistency 4/4, agentic_planning 4/4) so both models are equivalent for JSON/schema compliance and basic routing/decomposition. External math benchmarks (Epoch AI): GPT-4.1 Nano scores 70% on MATH Level 5 and 28.9% on AIME 2025 (Epoch AI); DeepSeek has no external math scores in the payload. These numbers show Nano has measurable math strengths on Epoch AI tasks but both models have tradeoffs depending on task type.

Costs (assumes total token traffic split 50/50 input/output): DeepSeek V3.1 Terminus input $0.21/mTok, output $0.79/mTok; GPT-4.1 Nano input $0.10/mTok, output $0.40/mTok. At 1M total tokens/month (500k in + 500k out) DeepSeek ≈ $500/month vs Nano ≈ $250/month (DeepSeek +$250). At 10M tokens/month DeepSeek ≈ $5,000 vs Nano ≈ $2,500 (gap $2,500). At 100M tokens/month DeepSeek ≈ $50,000 vs Nano ≈ $25,000 (gap $25,000). The priceRatio in the payload is ~1.975 — DeepSeek costs roughly 2× Nano. Teams with high-volume, latency-sensitive, or budget-constrained production should prioritize GPT-4.1 Nano; teams that need the long-context, strategic or multilingual edge and can absorb the extra $/month may prefer DeepSeek.

Choose DeepSeek V3.1 Terminus if: you must work reliably over very long contexts (30K+ tokens), need top-ranked strategic analysis or multilingual output, or prioritize creative problem solving for high-complexity prompts and can accept ~2× the cost. Choose GPT-4.1 Nano if: you want the best price-to-performance for general production, need stronger faithfulness, safer refusals, and better tool-calling/function orchestration, or must keep monthly AI spend low at scale.