GPT-5.1 vs Grok 4.20

Overview of our 12-test head-to-head: Grok 4.20 wins 2 tests, GPT-5.1 wins 1, and 9 are ties. Detailed walk-through:

• structured output: Grok 4.20 = 5 vs GPT-5.1 = 4. Grok ranks tied for 1st of 54 (display: "tied for 1st with 24 other models"), while GPT-5.1 is rank 26 of 54. This matters when you need strict JSON/schema compliance and format adherence (e.g., automated data pipelines, contracts or invoices).
• tool calling: Grok 4.20 = 5 vs GPT-5.1 = 4. Grok is tied for 1st on tool calling (display: "tied for 1st with 16 other models"), GPT-5.1 sits at rank 18 of 54. For function selection, argument accuracy and sequencing (agentic tool chains), Grok is the stronger choice in our tests.
• safety calibration: GPT-5.1 = 2 vs Grok 4.20 = 1; GPT-5.1 ranks 12 of 55 vs Grok rank 32. GPT-5.1 is better at refusing harmful requests while allowing legitimate ones in our evaluation.
• ties (both models scored the same): strategic analysis (5/5), constrained rewriting (4/5), creative problem solving (4/5), faithfulness (5/5), classification (4/5), long context (5/5), persona consistency (5/5), agentic planning (4/5), multilingual (5/5). Notably both models are tied for 1st on faithfulness, long context and multilingual by ranking displays.
• external benchmarks: GPT-5.1 additionally posts SWE-bench Verified = 68% and AIME 2025 = 88.6% (these are Epoch AI scores and reported as external benchmarks). Grok 4.20 has no SWE-bench or AIME scores in the payload, so GPT-5.1 shows stronger third-party math/coding evidence in our summary.
• context window and practical implications: Grok 4.20 supports a 2,000,000 token context window vs GPT-5.1's 400,000. Both scored 5/5 on long context in our suite, but Grok's larger window gives more headroom for single-session retrieval, multi-document analysis, or very large tool state. In short: Grok leads on structured outputs and tool calling (important for agentic pipelines and schema-driven APIs); GPT-5.1 leads on safety and has supporting external math/coding scores.

Raw per-mtok prices: GPT-5.1 output $10.00 / mtok, input $1.25 / mtok; Grok 4.20 output $6.00 / mtok, input $2.00 / mtok. GPT-5.1's output pricing is 1.6667x Grok's (priceRatio 1.6667). Example monthly costs (output-only basis):

• 1M tokens: GPT-5.1 = $10,000; Grok 4.20 = $6,000.
• 10M tokens: GPT-5.1 = $100,000; Grok 4.20 = $60,000.
• 100M tokens: GPT-5.1 = $1,000,000; Grok 4.20 = $600,000. If you assume input tokens equal output tokens (input+output):
• 1M tokens total I/O: GPT-5.1 = $11,250; Grok = $8,000.
• 10M: GPT-5.1 = $112,500; Grok = $80,000.
• 100M: GPT-5.1 = $1,125,000; Grok = $800,000. Who should care: any organization at >1M tokens/month will see meaningful dollar differences; at 10M–100M tokens the gap becomes strategic for budgeting. Choose Grok if per-token cost and large-scale usage are top priorities; choose GPT-5.1 if the extra cost is warranted by its safety calibration and external benchmark strengths.

Choose GPT-5.1 if: you prioritize safety calibration and third-party math/coding evidence (GPT-5.1: SWE-bench 68%, AIME 88.6%), need tight refusal behavior or you accept higher per-token costs for those strengths. Choose Grok 4.20 if: you build multi-tool agents, require strict schema/JSON outputs, need the largest context window (2,000,000 tokens), or must minimize cost per output token (Grok $6 vs GPT-5.1 $10 per mtok). Specific examples: use GPT-5.1 for moderated tutoring/coding assistants and high-assurance math workflows; use Grok 4.20 for production agentic pipelines, automated data transformation services, and high-volume chatbot deployments where cost and tool calling matter most.