by datastudy.nl

Head-to-head comparisons of frontier AI models, rebuilt daily from public benchmark data

Head to head

Grok 4.5 vs Claude Sonnet 5

How Grok 4.5 and Claude Sonnet 5 stack up across benchmarks, pricing, speed, and the workloads that matter.

Grok 4.5

xAI · Proprietary

Blended price$2.44per 1M tokens
Context500Ktokens
Speed4.4tok/s
Benchmarks14results
VS

Claude Sonnet 5

Anthropic · Proprietary

Blended price$2.89per 1M tokens
Context1Mtokens
Speed9.4tok/s
Benchmarks22results

Grok 4.5 is the cheaper of the two at $2.44 per million blended tokens, about 1.18x less than Claude Sonnet 5 at $2.89. On agents & tool use, Grok 4.5 leads by about 4 points in our normalized benchmark average.

The table below breaks down every workload axis where both models have published results. Each score is a normalized 0 to 1 average across the benchmarks tagged with that category. A gap of a few points is noise; a gap of ten or more is a real difference in capability. Where one model has not reported a result, the cell shows n/a and the missing benchmark does not drag its average down.

Benchmark scores by workload

WorkloadGrok 4.5Claude Sonnet 5Edge
Reasoning 70% 68% +1.9 pts
Coding 55% 56% +1 pts
Agents & tool use 54% 50% +4.3 pts
Math n/a 70% n/a
Vision & multimodal n/a 67% n/a
Knowledge & factuality 64% 74% +10.5 pts

The headline benchmarks below are the most widely cited individual tests. GPQA Diamond measures graduate-level reasoning in physics, chemistry, and biology. SWE-Bench Verified tests whether a model can fix real GitHub issues. MMMU-Pro covers college-level multimodal understanding across six disciplines. AIME and FrontierMath push competitive and research math. BrowseComp measures web research ability.

Headline benchmarks

BenchmarkGrok 4.5Claude Sonnet 5
GPQA 93% n/a
SWE-Bench Verified n/a 85%
Terminal-Bench 2.0 n/a 80%
BrowseComp n/a 85%

Benchmarks tell you what a model can do in a controlled setting. They do not tell you whether it will work on your specific task, with your specific data, at your specific scale. The recommendations below map each common workload to whichever of these two models scores higher on the relevant axis. Use them as a starting point, not a final answer.

Which should you choose?

Hard reasoning

Multi-step analysis, research, and problems that need sustained thought.

Grok 4.5

Coding & software

Writing, reviewing, and debugging code across a real codebase.

Claude Sonnet 5

Agents & tool use

Long-running agents that call tools, browse, and act on their own.

Grok 4.5

Math & science

Formal math, competitive problems, and quantitative science.

Claude Sonnet 5

Vision & documents

Reading images, screenshots, charts, and dense documents.

Claude Sonnet 5

High-volume & cost-sensitive

Cheap, repetitive calls where the blended token price dominates.

Grok 4.5

Low latency & interactive

Chat, autocomplete, and real-time experiences that need snappy responses.

Claude Sonnet 5

Scores are normalized from public benchmarks published by llm-stats.com and averaged per workload. Pricing is the blended input/output cost per million tokens at an 8:1 mix. Refreshes daily. How this works.