Claude Opus 4.7 vs Grok 4.1 Fast

Across our 12-test suite, Claude Opus 4.7 wins 4 benchmarks, Grok 4.1 Fast wins 3, and the two tie on 5.

Where Opus 4.7 leads:

• Tool calling: 5/5 vs 4/5. Opus 4.7 ties for 1st among 55 models; Grok 4.1 Fast ranks 19th of 55. For agentic workflows requiring precise function selection, argument accuracy, and multi-step sequencing, this gap matters.
• Agentic planning: 5/5 vs 4/5. Opus 4.7 ties for 1st among 55; Grok 4.1 Fast ranks 17th. Goal decomposition and failure recovery — critical for autonomous agent pipelines — favor Opus 4.7.
• Creative problem solving: 5/5 vs 4/5. Opus 4.7 ties for 1st among 55 models (9 total); Grok 4.1 Fast ranks 10th of 55. Generating non-obvious, specific, feasible ideas is a meaningful differentiator for product and strategy work.
• Safety calibration: 3/5 vs 1/5. This is the starkest gap. Opus 4.7 ranks 10th of 56 models; Grok 4.1 Fast ranks 33rd of 56 (scoring 1/5, in the bottom quarter of all models tested). Safety calibration measures both refusing harmful requests AND permitting legitimate ones — a score of 1 indicates significant miscalibration in our testing. This matters most for consumer-facing or compliance-sensitive deployments.

Where Grok 4.1 Fast leads:

• Structured output: 5/5 vs 4/5. Grok 4.1 Fast ties for 1st among 55 models (25 total); Opus 4.7 ranks 26th. JSON schema compliance and format adherence is table stakes for most API integrations — Grok 4.1 Fast has a genuine edge here.
• Classification: 4/5 vs 3/5. Grok 4.1 Fast ties for 1st among 54 models; Opus 4.7 ranks 31st. Accurate categorization and routing at 4/5 while Opus 4.7 scores 3/5 (below the median of 4) is a meaningful difference for document processing and triage systems.
• Multilingual: 5/5 vs 4/5. Grok 4.1 Fast ties for 1st among 56 models; Opus 4.7 ranks 36th. For non-English language output at equivalent quality, Grok 4.1 Fast is the clearer choice.

Ties (both models perform equally): Strategic analysis, constrained rewriting, faithfulness, long context, and persona consistency all score identically. Both models score 5/5 on faithfulness (sticking to source material) and long context (retrieval accuracy at 30K+ tokens), placing them tied for 1st in each. Strategic analysis is also a dead heat at 5/5 each.

Grok 4.1 Fast supports a 2 million token context window vs Opus 4.7's 1 million tokens — relevant for extremely long document processing, though both score equally on our long context benchmark.

Grok 4.1 Fast also exposes reasoning tokens (togglable), logprobs, and seed parameters — useful for reproducibility and interpretability in production systems. Opus 4.7 additionally accepts image inputs alongside text.

The cost gap between these two models is among the widest in our dataset. Claude Opus 4.7 runs $5 per million input tokens and $25 per million output tokens. Grok 4.1 Fast runs $0.20 per million input tokens and $0.50 per million output tokens — a 25x difference on input and 50x on output.

At 1 million output tokens per month, Opus 4.7 costs $25 vs $0.50 for Grok 4.1 Fast — a $24.50 gap that's barely noticeable. At 10 million output tokens, that becomes $250 vs $5 — still manageable for most teams. At 100 million output tokens, the gap reaches $2,500 vs $50 per month. At that scale, choosing Opus 4.7 over Grok 4.1 Fast for tasks where both score equally requires a concrete justification.

Who should care: developers building customer support systems, research pipelines, or classification tools — areas where Grok 4.1 Fast matches or beats Opus 4.7 on benchmarks — should default to Grok 4.1 Fast and reallocate the savings. Teams running complex agentic workflows where Opus 4.7's tool calling (5/5) and agentic planning (5/5) scores justify the premium should budget accordingly. For consumer-facing chat at scale, the cost difference is prohibitive unless you have a specific quality ceiling to meet.

Choose Claude Opus 4.7 if:

• You're building autonomous agents where tool calling accuracy and multi-step planning are critical — it scores 5/5 on both vs Grok 4.1 Fast's 4/5.
• Safety calibration is a hard requirement: Opus 4.7 scores 3/5 vs Grok 4.1 Fast's 1/5, making it significantly more appropriate for consumer-facing or compliance-sensitive applications.
• Your workflow demands creative problem solving or ideation at the highest tier (5/5 vs 4/5).
• You need image understanding alongside text — Opus 4.7 accepts image inputs per our data.
• Volume is low enough that the 50x output cost premium ($25 vs $0.50 per million tokens) is not a budget constraint.

Choose Grok 4.1 Fast if:

• You're processing structured data, building classification systems, or routing documents — it scores 5/5 on structured output and 4/5 on classification vs Opus 4.7's 4/5 and 3/5.
• Your application serves non-English users — Grok 4.1 Fast scores 5/5 on multilingual vs 4/5.
• You're running at scale (10M+ output tokens/month) and the $2,000+ monthly savings per 100M tokens are material to your budget.
• You need a 2 million token context window for extremely long document processing.
• You require logprobs, seed parameters, or reasoning token control for production reproducibility and interpretability.
• You need a capable agentic model at a price point that makes experimentation economical — it scores 4/5 on both tool calling and agentic planning, which ties or beats most models in our 53-model dataset.