💰 Unit Cost Winner Gemini 3.1 Pro $1.25/1M in · $10.00/1M out
⚡ Latency & Speed Winner Gemini 3.1 Pro 420ms TTFT · 98 tok/s
💻 Coding (SWE) Winner Gemini 3.1 Pro 71.8% SWE-bench · 94.8% HumanEval
🧠 STEM Reasoning Winner Gemini 3.1 Pro 82.4% GPQA · 96.8% MATH-500

Which model is better: Claude 3.7 Sonnet or Gemini 3.1 Pro?

Gemini 3.1 Pro is 58.3% cheaper for input tokens ($1.25 vs. $3.00 per 1M tokens) and $10.00 vs. $15.00 for output tokens (2.4x cost advantage). In terms of operational performance, Gemini 3.1 Pro delivers lower response latency at 420ms TTFT (120ms faster than Claude 3.7 Sonnet) with 98 vs. 72 tok/s throughput. Gemini 3.1 Pro leads coding evaluations at 71.8% SWE-bench Verified vs. 70.3% for Claude 3.7 Sonnet and 82.4% vs. 78.5% 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 3.7 Sonnet Gemini 3.1 Pro Net Delta / Advantage
Input Cost / 1M Tokens $3.00 $1.25 Gemini 3.1 Pro is 2.4x cheaper
Output Cost / 1M Tokens $15.00 $10.00 Gemini 3.1 Pro (33.3% lower)
Prompt Cache Read / 1M $0.300 $0.310 Claude 3.7 Sonnet is 1.0x cheaper
Prompt Cache Write / 1M $3.75 $1.25 Gemini 3.1 Pro is 3.0x cheaper
Context Window (Max Output) 205k (64k out) 1,049k (66k out) Gemini 3.1 Pro (5.1x larger context)
Avg TTFT Response Latency 540ms 420ms Gemini 3.1 Pro (120ms faster)
Generation Speed (Throughput) 72 tok/s 98 tok/s Gemini 3.1 Pro (+26 tok/s faster)
SWE-bench Verified (Coding) 70.3% 71.8% Gemini 3.1 Pro (+1.5% lead)
GPQA Diamond (PhD STEM) 78.5% 82.4% Gemini 3.1 Pro (+3.9% lead)
MMLU-Pro (Multi-Discipline) 88% 89.5% Gemini 3.1 Pro (+1.5% lead)
MATH-500 (Quantitative Logic) 96.2% 96.8% Gemini 3.1 Pro (+0.6% lead)
Inference Value Score (IVR) 54.3 / 100 60 / 100 Gemini 3.1 Pro (+5.7 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 3.1 Pro $69.50

$1.25/1M in · $10.00/1M out

Prompt Cache: $0.310/1M read · $1.25/1M write

Projected Monthly Cost Reduction
$46.75 / mo
(40.2% lower cost with Gemini 3.1 Pro)
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 3.1 Pro

Choose Gemini 3.1 Pro (Google) for complex enterprise architecture planning, multi-file code refactoring, legal/financial corpus auditing, and multimodal research — offering a 1,048k context window, 420ms TTFT, and $1.25/1M input pricing ($0.310/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Claude 3.7 Sonnet or Gemini 3.1 Pro?

Gemini 3.1 Pro is cheaper at $1.25/1M 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 3.1 Pro?

Gemini 3.1 Pro delivers faster first-token latency at 420ms TTFT (98 tok/s throughput) compared to 540ms TTFT (72 tok/s) for Claude 3.7 Sonnet.

How do Claude 3.7 Sonnet and Gemini 3.1 Pro compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Claude 3.7 Sonnet scores 70.3% versus 71.8% for Gemini 3.1 Pro. On GPQA Diamond graduate-level STEM reasoning, Claude 3.7 Sonnet scores 78.5% versus 82.4% for Gemini 3.1 Pro (and 96.2% vs 96.8% 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 3.1 Pro?

Choose Gemini 3.1 Pro (Google) for complex enterprise architecture planning, multi-file code refactoring, legal/financial corpus auditing, and multimodal research — offering a 1,048k context window, 420ms TTFT, and $1.25/1M input pricing ($0.310/1M cached reads).

Explore High-Priority Related Model Matchups