💰 Unit Cost Winner Gemini 4 Argon $2.00/1M in · $10.00/1M out
⚡ Latency & Speed Winner Claude 3.7 Sonnet 540ms TTFT · 72 tok/s
💻 Coding (SWE) Winner Gemini 4 Argon 84.5% SWE-bench · 96.3% HumanEval
🧠 STEM Reasoning Winner Gemini 4 Argon 93.8% GPQA · 98.2% MATH-500

Which model is better: Claude 3.7 Sonnet or Gemini 4 Argon?

Gemini 4 Argon delivers superior capability at a 33.3% lower cost, while Claude 3.7 Sonnet only leads in latency. Priced at $2.00/$10.00 per 1M tokens versus Claude's $3.00/$15.00, Gemini dominates SWE-bench Verified (84.5% vs. 70.3%), GPQA Diamond (93.8% vs. 78.5%), and throughput (115 vs. 72 tok/s). However, Claude hits a 540ms TTFT, 310ms faster.
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 3.7 Sonnet Gemini 4 Argon Net Delta / Advantage
Input Cost / 1M Tokens $3.00 $2.00 Gemini 4 Argon is 1.5x cheaper
Output Cost / 1M Tokens $15.00 $10.00 Gemini 4 Argon (33.3% lower)
Prompt Cache Read / 1M $0.300 $0.100 Gemini 4 Argon is 3.0x cheaper
Prompt Cache Write / 1M $3.75 $0.50 Gemini 4 Argon is 7.5x cheaper
Context Window (Max Output) 205k (64k out) 1,024k (1000k out) Gemini 4 Argon (5.0x larger context)
Avg TTFT Response Latency 540ms 850ms Claude 3.7 Sonnet (310ms faster)
Generation Speed (Throughput) 72 tok/s 115 tok/s Gemini 4 Argon (+43 tok/s faster)
SWE-bench Verified (Coding) 70.3% 84.5% Gemini 4 Argon (+14.2% lead)
GPQA Diamond (PhD STEM) 78.5% 93.8% Gemini 4 Argon (+15.3% lead)
MMLU-Pro (Multi-Discipline) 88% 91.4% Gemini 4 Argon (+3.4% lead)
MATH-500 (Quantitative Logic) 96.2% 98.2% Gemini 4 Argon (+2.0% lead)
Inference Value Score (IVR) 54.3 / 100 62.6 / 100 Gemini 4 Argon (+8.3 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 3.7 Sonnet $116.25

$3.00/1M in · $15.00/1M out

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

Gemini 4 Argon $76.25

$2.00/1M in · $10.00/1M out

Prompt Cache: $0.100/1M read · $0.50/1M write

Projected Monthly Cost Reduction
$40.00 / mo
(34.4% lower cost with Gemini 4 Argon)
Open Full Matchup Analysis →
A

When to Choose Claude 3.7 Sonnet

Choose Claude 3.7 Sonnet (Anthropic) for full-stack repository development, complex code refactoring, and agentic tool use with predictable prompt cache economics — offering a 204k context window, 540ms TTFT, and $3.00/1M input pricing ($0.300/1M cached reads).

B

When to Choose Gemini 4 Argon

Choose Gemini 4 Argon (Google) for engineered with a 1M output token limit for long-horizon software engineering, cybersecurity vulnerability remediation, and deep multimodal enterprise work across legal and financial domains — offering a 1,024k context window, 850ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Claude 3.7 Sonnet or Gemini 4 Argon?

Gemini 4 Argon is cheaper at $2.00/1M input tokens ($10.00/1M output) compared to $3.00/1M input ($15.00/1M output) for Claude 3.7 Sonnet.

Which model has lower TTFT latency and higher tok/s throughput: Claude 3.7 Sonnet or Gemini 4 Argon?

Claude 3.7 Sonnet delivers faster first-token latency at 540ms TTFT (72 tok/s throughput) compared to 850ms TTFT (115 tok/s) for Gemini 4 Argon.

How do Claude 3.7 Sonnet and Gemini 4 Argon compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Claude 3.7 Sonnet scores 70.3% versus 84.5% for Gemini 4 Argon. On GPQA Diamond graduate-level STEM reasoning, Claude 3.7 Sonnet scores 78.5% versus 93.8% for Gemini 4 Argon (and 96.2% vs 98.2% on MATH-500).

When should you choose Claude 3.7 Sonnet?

Choose Claude 3.7 Sonnet (Anthropic) for full-stack repository development, complex code refactoring, and agentic tool use with predictable prompt cache economics — offering a 204k context window, 540ms TTFT, and $3.00/1M input pricing ($0.300/1M cached reads).

When should you choose Gemini 4 Argon?

Choose Gemini 4 Argon (Google) for engineered with a 1M output token limit for long-horizon software engineering, cybersecurity vulnerability remediation, and deep multimodal enterprise work across legal and financial domains — offering a 1,024k context window, 850ms TTFT, and $2.00/1M input pricing ($0.100/1M cached reads).

Explore High-Priority Related Model Matchups