DeepSeek V3.1 Terminus vs Grok 4.1 Fast

Summary of our 12-test head-to-head (scores are from our testing):

• Grok wins (decisive): constrained_rewriting 4 vs 3 (Grok ranks 6 of 53 vs DeepSeek rank 31 of 53) — means Grok is noticeably better at tight compression and strict character-limit rewrites. tool_calling 4 vs 3 (Grok rank 18/54 vs DeepSeek 47/54) — Grok is stronger at function selection, argument accuracy and sequencing in practical tool/agent flows. faithfulness 5 vs 3 (Grok tied for 1st vs DeepSeek rank 52/55) — Grok sticks to source material far more reliably. classification 4 vs 3 (Grok tied for 1st vs DeepSeek rank 31/53) — Grok is better at routing and categorization. persona_consistency 5 vs 4 (Grok tied for 1st vs DeepSeek rank 38/53) — Grok more robustly maintains persona and resists injection.
• Ties (both models scored the same): structured_output 5/5 (both tied for 1st) — both are excellent at JSON/schema compliance; strategic_analysis 5/5 (tied for 1st) — both produce strong tradeoff reasoning with numbers; creative_problem_solving 4/4 (both rank 9/54) — equal ability to generate feasible, non-obvious ideas; long_context 5/5 (both tied for 1st) — both handle 30K+ token retrieval tasks at top-tier levels; safety_calibration 1/1 (both rank 32/55) — both underperform on refusing harmful requests; agentic_planning 4/4 (both rank 16/54) — both handle goal decomposition and recovery similarly; multilingual 5/5 (both tied for 1st) — equivalent cross-language quality.
• No metrics where DeepSeek decisively beats Grok; DeepSeek’s strengths are largely ties on long_context, structured_output, strategic_analysis and creative_problem_solving (scores of 5 or 4), meaning it matches Grok on those tasks but loses on tool-calling, faithfulness, classification and constrained rewriting. Practical implication: choose Grok where you need reliable tool/agent behavior, accurate categorization, and low hallucination; choose either model for schema output and very long context work. Note: both models scored 1 on safety_calibration in our testing, so add guardrails for safety-sensitive deployments.

Per the payload, DeepSeek V3.1 Terminus charges $0.21 input + $0.79 output = $1.00 per 1k tokens; Grok 4.1 Fast charges $0.20 input + $0.50 output = $0.70 per 1k tokens. At 1M tokens/month (1,000 mTok) that’s DeepSeek $1,000 vs Grok $700 (save $300). At 10M tokens: DeepSeek $10,000 vs Grok $7,000 (save $3,000). At 100M tokens: DeepSeek $100,000 vs Grok $70,000 (save $30,000). The 1.58x priceRatio means high-volume deployments (customer support routing, large-scale retrieval, continuous inference) will see material savings with Grok; teams with small-scale or specialized needs may tolerate DeepSeek’s premium for parity on some metrics but should budget accordingly.

Choose DeepSeek V3.1 Terminus if: you specifically need top-tier long-context (5/5) and structured-output (5/5) performance and are willing to pay ~1.58× the per-token cost for parity on those tasks. Choose Grok 4.1 Fast if: you need better tool-calling (4 vs 3), higher faithfulness (5 vs 3), stronger classification (4 vs 3), persona consistency (5 vs 4), constrained rewriting (4 vs 3), multimodal inputs and a much larger context window (2,000,000 tokens) — and you want lower output cost ($0.50 vs $0.79 per mTok). For production agentic pipelines and large-volume usage, Grok is the practical winner; for niche workflows that only require the tied strengths and can absorb higher cost, DeepSeek is acceptable.