DeepSeek V3.1 vs Grok 4

We ran both models across our 12-test suite and report scores (1-5) and rankings from our testing. Summary: Grok 4 wins 6 tests, DeepSeek V3.1 wins 3, and 3 tests tie. Detailed walk-through: 1) Faithfulness — tie (both score 5). Both models tied for 1st on faithfulness in our tests, so expect strong source fidelity from either. 2) Constrained rewriting — Grok 4 wins (Grok 4 = 4 vs DeepSeek = 3). Grok ranks 6th of 53 on constrained rewriting, so it better compresses content into tight character limits for real products. 3) Safety calibration — Grok 4 wins (2 vs 1). Grok ranks 12th of 55 on safety calibration in our testing, meaning it is more likely to refuse harmful prompts appropriately. 4) Tool calling — Grok 4 wins (4 vs 3). Grok ranks 18th of 54 vs DeepSeek at rank 47; for function selection, argument accuracy, and sequencing Grok is substantially better in our tests. 5) Structured output — DeepSeek V3.1 wins (5 vs 4). DeepSeek is tied for 1st on JSON schema compliance, so it’s preferable when strict format adherence is required. 6) Agentic planning — DeepSeek V3.1 wins (4 vs 3). DeepSeek ranks 16th vs Grok at 42nd, indicating stronger goal decomposition and recovery for multi-step plans. 7) Multilingual — Grok 4 wins (5 vs 4). Grok is tied for 1st on multilingual performance; choose it for non-English parity. 8) Classification — Grok 4 wins (4 vs 3). Grok is tied for 1st on classification, so it routes and labels inputs more reliably in our tests. 9) Long context — tie (both 5). Both models tied for 1st on long-context retrieval accuracy in our suite; however, note Grok’s numeric context window is 256,000 tokens vs DeepSeek’s 32,768 tokens. 10) Persona consistency — tie (both 5). Both maintain personas well in our testing. 11) Strategic analysis — Grok 4 wins (5 vs 4). Grok is tied for 1st on nuanced tradeoff reasoning in our tests, useful where numeric tradeoffs matter. 12) Creative problem solving — DeepSeek V3.1 wins (5 vs 3). DeepSeek is tied for 1st on producing non-obvious, feasible ideas in our testing. Bottom-line interpretation: Grok 4 is stronger for classification, tool-driven agents, multilingual and safety-sensitive apps. DeepSeek V3.1 is superior for structured outputs, creative ideation, and budget-sensitive long-context tasks.

Combine input+output costs to compare real usage. DeepSeek V3.1: $0.15 + $0.75 = $0.90 per million tokens. Grok 4: $3 + $15 = $18.00 per million tokens. At 1M tokens/month: DeepSeek ≈ $0.90 vs Grok ≈ $18. At 10M tokens: DeepSeek ≈ $9 vs Grok ≈ $180. At 100M tokens: DeepSeek ≈ $90 vs Grok ≈ $1,800. The gap matters for consumer apps, high-throughput APIs, and automated pipelines where token volumes scale to tens or hundreds of millions — DeepSeek reduces monthly inference spend dramatically. Teams building mission-critical, tool-rich agents or multi-language classifiers may justify Grok's higher cost for the benchmarked quality gains; cost-sensitive startups and large-scale content or ideation workloads should prefer DeepSeek for lower TCO.

Choose DeepSeek V3.1 if you need cost-efficient, creative, and schema-compliant output at scale — ideal for large-volume content generation, creative ideation pipelines, or strict JSON outputs (structured_output=5, creative_problem_solving=5, combined cost ≈ $0.90/M-token). Choose Grok 4 if you need robust tool calling, strategic analysis, multilingual parity, and stronger safety/calibration for production agents or classification services (Grok wins 6/12 benchmarks, tool_calling=4, strategic_analysis=5) and can absorb the higher cost (~$18/M-token). If you need both, consider hybrid routing: use DeepSeek for bulk generation/creativity and Grok for final classification, tool execution, or safety-critical steps.