💰 Unit Cost Winner Grok 4 $2.50/1M in · $12.50/1M out
⚡ Latency & Speed Winner Claude 3.5 Sonnet 310ms TTFT · 80 tok/s
💻 Coding (SWE) Winner Grok 4 73.2% SWE-bench · 95% HumanEval
🧠 STEM Reasoning Winner Grok 4 86.2% GPQA · 97.6% MATH-500

Which model is better: Claude 3.5 Sonnet or Grok 4?

Grok 4 is 16.7% cheaper for input tokens ($2.50 vs. $3.00 per 1M tokens) and $12.50 vs. $15.00 for output tokens (1.2x cost advantage). In terms of operational performance, Claude 3.5 Sonnet delivers lower response latency at 310ms TTFT (170ms faster than Grok 4) with 80 vs. 95 tok/s throughput. Grok 4 leads coding evaluations at 73.2% SWE-bench Verified vs. 49.0% for Claude 3.5 Sonnet and 86.2% vs. 59.4% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.

Verified Performance & Unit Economics Delta (12 Dimensions)

Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.

Metric / Dimension Claude 3.5 Sonnet Grok 4 Net Delta / Advantage
Input Cost / 1M Tokens $3.00 $2.50 Grok 4 is 1.2x cheaper
Output Cost / 1M Tokens $15.00 $12.50 Grok 4 (16.7% lower)
Prompt Cache Read / 1M $0.300 $0.500 Claude 3.5 Sonnet is 1.7x cheaper
Prompt Cache Write / 1M $3.75 $2.50 Grok 4 is 1.5x cheaper
Context Window (Max Output) 205k (8k out) 262k (66k out) Grok 4 (1.3x larger context)
Avg TTFT Response Latency 310ms 480ms Claude 3.5 Sonnet (170ms faster)
Generation Speed (Throughput) 80 tok/s 95 tok/s Grok 4 (+15 tok/s faster)
SWE-bench Verified (Coding) 49% 73.2% Grok 4 (+24.2% lead)
GPQA Diamond (PhD STEM) 59.4% 86.2% Grok 4 (+26.8% lead)
MMLU-Pro (Multi-Discipline) 78% 89.9% Grok 4 (+11.9% lead)
MATH-500 (Quantitative Logic) 78.3% 97.6% Grok 4 (+19.3% lead)
Inference Value Score (IVR) 46.2 / 100 57.6 / 100 Grok 4 (+11.4 pts)

Interactive Monthly Token Economics & ROI Forecaster

Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.

25.0M Tokens
500K 50M 250M 500M+
5.0M Tokens
100K 25M 75M 150M+
50% Cached
0% (Uncached) 25% 50% (Typical Agent) 95% Max

Estimated Monthly Spend

Claude 3.5 Sonnet $116.25

$3.00/1M in · $15.00/1M out

Prompt Cache: $0.300/1M read · $3.75/1M write

Grok 4 $100.00

$2.50/1M in · $12.50/1M out

Prompt Cache: $0.500/1M read · $2.50/1M write

Projected Monthly Cost Reduction
$16.25 / mo
(14.0% lower cost with Grok 4)
Open Full Matchup Analysis →
A

When to Choose Claude 3.5 Sonnet

Choose Claude 3.5 Sonnet (Anthropic) for legacy enterprise workflows, code review pipelines, and human-like content generation — offering a 204k context window, 310ms TTFT, and $3.00/1M input pricing ($0.300/1M cached reads).

B

When to Choose Grok 4

Choose Grok 4 (xAI) for real-time financial/market intelligence, PhD-level STEM problem solving, and autonomous code generation — offering a 262k context window, 480ms TTFT, and $2.50/1M input pricing ($0.500/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Claude 3.5 Sonnet or Grok 4?

Grok 4 is cheaper at $2.50/1M input tokens ($12.50/1M output) compared to $3.00/1M input ($15.00/1M output) for Claude 3.5 Sonnet.

Which model has lower TTFT latency and higher tok/s throughput: Claude 3.5 Sonnet or Grok 4?

Claude 3.5 Sonnet delivers faster first-token latency at 310ms TTFT (80 tok/s throughput) compared to 480ms TTFT (95 tok/s) for Grok 4.

How do Claude 3.5 Sonnet and Grok 4 compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Claude 3.5 Sonnet scores 49% versus 73.2% for Grok 4. On GPQA Diamond graduate-level STEM reasoning, Claude 3.5 Sonnet scores 59.4% versus 86.2% for Grok 4 (and 78.3% vs 97.6% on MATH-500).

When should you choose Claude 3.5 Sonnet?

Choose Claude 3.5 Sonnet (Anthropic) for legacy enterprise workflows, code review pipelines, and human-like content generation — offering a 204k context window, 310ms TTFT, and $3.00/1M input pricing ($0.300/1M cached reads).

When should you choose Grok 4?

Choose Grok 4 (xAI) for real-time financial/market intelligence, PhD-level STEM problem solving, and autonomous code generation — offering a 262k context window, 480ms TTFT, and $2.50/1M input pricing ($0.500/1M cached reads).

Explore High-Priority Related Model Matchups