SWE-Bench Pro<\/strong><\/td>Repository-level coding<\/td> Not directly comparable<\/td> Not published<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nWhere a cell says “not published” or “not confirmed,” that reflects the actual state of public data, not an oversight.<\/p>\n\n\n\n
Original Logic Puzzle Tests<\/h2>\n\n\n\n These five puzzles are original and illustrative, not scientific trials. They show reasoning style, not final rankings.<\/p>\n\n\n\n
Note:<\/strong> The \u201cGrok style\u201d answers below are illustrative simulations based on documented Grok capabilities. They are not actual Grok 4.6 outputs<\/strong> and should not be presented as benchmark results or direct model responses.<\/p>\n\n\n\nPuzzle 1: The Three Boxes<\/h3>\n\n\n\n Three boxes are labeled “Apples,” “Oranges,” and “Mixed.” Every label is wrong. You may pick one fruit from one box to identify all three correctly. Which box do you pick from?<\/p>\n\n\n\n
Grok-style answer:<\/strong> Pick from the box labeled “Mixed,” since it cannot actually be mixed, then deduce the rest by elimination.<\/p>\n\n\n\nClaude-style answer:<\/strong> Same core deduction, with an explicit written chain showing why each remaining label must resolve the way it does.<\/p>\n\n\n\nComparison:<\/strong> Both models reach the correct answer in testing of comparable prior-generation models. Claude’s documented style tends to show more explicit intermediate steps.<\/p>\n\n\n\nWinner:<\/strong> Tie on the final answer; Claude’s Sonnet-line explanations are typically more auditable, per Anthropic’s own agentic reasoning descriptions.<\/p>\n\n\n\nPuzzle 2: The Scheduling Constraint<\/h3>\n\n\n\n Five people need a meeting slot. Each has two blocked hours out of an eight-hour day, and no two people share both blocks. Can everyone attend the same one-hour slot?<\/p>\n\n\n\n
Grok-style answer:<\/strong> Fast constraint elimination, arriving at a valid hour quickly given Grok’s documented strength in agentic, tool-heavy tasks.<\/p>\n\n\n\nClaude-style answer:<\/strong> Builds a small table of blocked hours per person before eliminating, favoring a slower, more structured approach.<\/p>\n\n\n\nComparison:<\/strong> This is a constraint satisfaction puzzle, the category where structured, stepwise elimination reduces silent mistakes.<\/p>\n\n\n\nWinner:<\/strong> Claude Sonnet 5’s structured tabulation habit, described in its own system card as improved agentic search behavior, likely reduces error risk here.<\/p>\n\n\n\nPuzzle 3: The Sequence Pattern<\/h3>\n\n\n\n What comes next: 2, 6, 12, 20, 30, ?<\/p>\n\n\n\n
Grok-style answer:<\/strong> Recognizes the n(n+1) pattern quickly, consistent with strong published coding and pattern-heavy benchmark scores.<\/p>\n\n\n\nClaude-style answer:<\/strong> Same recognition, with a brief explanation of the difference sequence (4, 6, 8, 10) before stating the rule.<\/p>\n\n\n\nComparison:<\/strong> Pure pattern recognition puzzles like this are usually solved correctly by both current-generation frontier models.<\/p>\n\n\n\nWinner:<\/strong> Tie. This puzzle type is not where the two models are likely to separate meaningfully.<\/p>\n\n\n\nPuzzle 4: The Lateral Thinking Riddle<\/h3>\n\n\n\n A man lives on the tenth floor. Every day he takes the elevator down to the ground floor. Coming home, he takes it to the seventh floor and walks the rest, except on rainy days, when he goes to the tenth floor directly. Why?<\/p>\n\n\n\n
Grok-style answer:<\/strong> May require a nudge toward the “he’s too short to reach the button” explanation without the umbrella detail prompt.<\/p>\n\n\n\nClaude-style answer:<\/strong> Anthropic’s documentation of Sonnet 5 emphasizes broader instruction-following and content quality, which tends to help lateral riddles that hinge on reading between the lines.<\/p>\n\n\n\nComparison:<\/strong> Lateral thinking puzzles depend on reframing, a category with less clean benchmark coverage industry-wide.<\/p>\n\n\n\nWinner:<\/strong> Genuinely uncertain without formal testing. Treat this as an open question, not a settled one.<\/p>\n\n\n\nPuzzle 5: The Multi-Step Deduction Chain<\/h3>\n\n\n\nRow of five icons representing original logic puzzle test cases<\/figcaption><\/figure>\n\n\n\nFour friends finish a race in some order. Alex is not first. Bo finishes right after Alex. Cameron is not last. Drew beats Cameron. Who wins?<\/p>\n\n\n\n
Grok-style answer:<\/strong> Likely solves it through fast elimination given documented strength on structured logic tasks in xAI’s own materials.<\/p>\n\n\n\nClaude-style answer:<\/strong> Anthropic’s Terminal-Bench 2.1 gains suggest improved multi-step task execution, which is exactly what chained deduction puzzles require.<\/p>\n\n\n\nComparison:<\/strong> Multi-step deduction chains are where published Sonnet 5 benchmark gains (Terminal-Bench, HLE) most directly apply.<\/p>\n\n\n\nWinner:<\/strong> Based on published multi-step benchmark gains, Claude Sonnet 5 has a documented edge here, though this is inferred from benchmarks, not a direct puzzle-by-puzzle test.<\/p>\n\n\n\nConsistency, Error Recovery, and Hallucination Rate<\/h2>\n\n\n\n Getting one puzzle right is not the same as being consistently reliable.<\/p>\n\n\n\n
Anthropic reports that developers preferred Sonnet 5 over Sonnet 4.6 in real Claude Code sessions roughly 82% of the time in early internal comparisons, citing fewer hallucinated completions.<\/p>\n\n\n\n
xAI’s own published Grok 4.6 material highlights minimal hallucination and configurable reasoning effort as headline design goals, per multiple independent developer guides.<\/p>\n\n\n\n
Error recovery, catching a wrong mid-puzzle assumption, is harder to benchmark formally and mostly shows up in qualitative testing rather than leaderboard scores.<\/p>\n\n\n\n
Neither company currently publishes a dedicated “logic puzzle hallucination rate” metric, so claims here should stay cautious.<\/p>\n\n\n\n
Speed and Reasoning Effort<\/h2>\n\n\n\n Both models now support adjustable reasoning effort, trading speed for depth.<\/p>\n\n\n\n
Grok 4.6 is designed for fast, agentic workloads and is available with configurable reasoning effort. <\/p>\n\n\n\n
However, reliable apples-to-apples figures for tokens-per-second and total output tokens across Grok 4.6 and Claude Sonnet 5 depend on the API, workload, reasoning setting, and measurement method, so raw speed claims should be treated cautiously.<\/p>\n\n\n\n
Claude Sonnet 5’s higher effort settings, per DataCamp’s developer breakdown, can approach Opus 4.8 quality on certain benchmarks but at higher cost and slower output.<\/p>\n\n\n\n
For logic puzzles specifically, speed matters less than depth, since a fast wrong answer is still wrong.<\/p>\n\n\n\n
Table: Speed and Cost Snapshot<\/strong><\/p>\n\n\n\nModel<\/th> Input Price (per 1M tokens)<\/th> Output Price (per 1M tokens)<\/th> Context Window<\/th><\/tr><\/thead> Claude Sonnet 5<\/strong><\/td>$2.00<\/strong><\/td>$10.00<\/strong><\/td>1M tokens<\/td><\/tr> Grok 4.6<\/strong><\/td>$2.00<\/strong><\/td>$6.00<\/strong><\/td>500K tokens<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nReal-World Use Cases<\/h2>\n\n\n\nIllustration of real-world logic reasoning use cases in scheduling and coding<\/figcaption><\/figure>\n\n\n\nLogic puzzle strength usually translates to practical tasks beyond riddles.<\/p>\n\n\n\n
\nScheduling and constraint problems in operations tools.<\/li>\n\n\n\n Debugging code logic where multiple conditions interact.<\/li>\n\n\n\n Verifying contract clauses against each other for contradictions.<\/li>\n\n\n\n Structuring multi-step research plans for agentic workflows.<\/li>\n<\/ul>\n\n\n\nClaude Sonnet 5’s documented Terminal-Bench and agentic search gains suggest an edge in multi-step operational logic tasks.<\/p>\n\n\n\n
Grok 4.6’s documented strengths in agentic workflows, coding, and long-running tasks, combined with its relatively low output-token cost, make it a practical option for high-volume workloads where tool use and efficiency matter.<\/p>\n\n\n\n
Strengths and Weaknesses<\/h2>\n\n\n\n Table: Strengths and Weaknesses<\/strong><\/p>\n\n\n\nModel<\/th> Strengths<\/th> Weaknesses<\/th><\/tr><\/thead> Claude Sonnet 5<\/strong><\/td>Strong published reasoning and coding results; 1M-token context window; strong performance on complex multi-step tasks<\/td> Higher output cost than Grok 4.6; performance can vary with reasoning effort<\/td><\/tr> Grok 4.6<\/strong><\/td>Stronger agentic and coding capabilities; 500K-token context window; configurable reasoning effort; published results across multiple agentic and coding benchmarks; $6\/M output tokens<\/td> Dedicated logic-puzzle benchmark results are limited; published benchmark scores are not directly comparable across every evaluation<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nWho Should Choose Grok?<\/h2>\n\n\n\n Choose the Grok line<\/strong> if your workload is high-volume, cost-sensitive, and heavily dependent on tool calling or agentic workflows.<\/p>\n\n\n\nGrok 4.6<\/strong> is designed for coding, agentic tasks, knowledge work, and long-running workflows. Its $6 per million output-token pricing and configurable reasoning effort can also make it relevant for teams balancing capability with usage costs.<\/p>\n\n\n\nFor logic-heavy workloads, however, compare models using the same prompts, reasoning settings, and evaluation criteria rather than relying solely on general benchmark scores.<\/p>\n\n\n\n
Who Should Choose Claude Sonnet 5?<\/h2>\n\n\n\n Choose Claude Sonnet 5 if your logic tasks are complex, multi-step, and need an auditable reasoning trail.<\/p>\n\n\n\n
Its documented Terminal-Bench and HLE gains, plus a 1M-token context window, suit long, constraint-heavy documents and multi-stage agent workflows.<\/p>\n\n\n\n
Both models are publicly available and have published documentation and evaluation results. Claude Sonnet 5 has a public system card, while xAI has published Grok 4.6’s model documentation and benchmark results. <\/p>\n\n\n\n
Because their evaluation methods and reported benchmarks differ, direct comparisons should be interpreted in context.<\/p>\n\n\n\n
Final Verdict<\/h2>\n\n\n\n For logic puzzles today, both Claude Sonnet 5 and Grok 4.6 have publicly documented capabilities and evaluation results, but there is limited directly comparable benchmark data focused specifically on logic puzzles.<\/p>\n\n\n\n
Claude Sonnet 5 has published multi-step reasoning evaluations and a public system card, while Grok 4.6 has published results across several reasoning, coding, and agentic benchmarks.<\/p>\n\n\n\n
Grok 4.5 remains relevant when examining its documented performance and lower token costs, but Grok 4.6 is now the more current Grok model for comparisons.<\/p>\n\n\n\n
For a meaningful logic-puzzle comparison, the strongest approach is to test Claude Sonnet 5 and Grok 4.6 using the same puzzles, prompts, reasoning settings, and scoring criteria rather than relying on unrelated benchmark scores.<\/p>\n\n\n\n
FAQs<\/h2>\n\n\n\n Is Grok 4.6 released yet?<\/strong> Yes. Grok 4.6 was officially released on August 12, 2026. xAI has published its model documentation, pricing, and benchmark results, so it should now be treated as a publicly available model rather than a future release.<\/p>\n\n\n\nWhich model is better at logic puzzles right now, Grok or Claude?<\/strong> There is no single directly comparable public benchmark that establishes a definitive winner for logic puzzles. <\/p>\n\n\n\nClaude Sonnet 5 has published multi-step reasoning evaluations, while Grok 4.6 has published results across reasoning, coding, and agentic benchmarks. For logic puzzles specifically, comparing both models on the same set of puzzles and scoring criteria provides a more meaningful assessment.<\/p>\n\n\n\n
What benchmark best measures logic puzzle ability?<\/strong> No single benchmark fully covers logic puzzles. ARC-AGI-2 tests abstract pattern reasoning, while Humanity’s Last Exam and Terminal-Bench cover broader multi-step reasoning.<\/p>\n\n\n\nDoes Claude Sonnet 5 use chain-of-thought reasoning?<\/strong> Claude Sonnet 5 uses an adaptive thinking architecture with adjustable reasoning effort levels, allowing deeper step-by-step reasoning on harder tasks when needed.<\/p>\n\n\n\nIs Grok 4.6 good at constraint satisfaction puzzles?<\/strong> Grok 4.6 shows strong reasoning and coding capabilities, but xAI has not published a dedicated constraint-satisfaction benchmark.<\/p>\n\n\n\nHow much does Claude Sonnet 5 cost per logic puzzle query?<\/strong> Pricing is $2 per million input tokens and $10 per million output tokens through August 31, 2026, then $3 and $15 afterward, per Anthropic’s official pricing page.<\/p>\n\n\n\nCan I test these models myself on logic puzzles?<\/strong> Yes. Both offer API access, so you can run identical puzzle prompts against each model and compare outputs directly for your own use case.<\/p>\n\n\n\n
![\"compare](\"https:\/\/aizolo.com\/blog\/wp-content\/uploads\/2026\/02\/compare-grok-4.6-and-claude-Sonnet-5-for-logic-puzzles-1024x683.png\" "\\"\\"")