Which model is better: Claude 3.7 Sonnet or GPT-6 Astra?
Claude 3.7 Sonnet is 70.0% cheaper for input tokens ($3.00 vs. $10.00 per 1M tokens) and $15.00 vs. $50.00 for output tokens (3.3x cost advantage). In terms of operational performance, Claude 3.7 Sonnet delivers lower response latency at 540ms TTFT (200ms faster than GPT-6 Astra) with 72 vs. 74 tok/s throughput. GPT-6 Astra leads coding evaluations at 75.7% SWE-bench Verified vs. 70.3% for Claude 3.7 Sonnet and 96.0% vs. 78.5% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.
Zero-Shot RAG Verified
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
GPT-6 Astra
Net Delta / Advantage
Input Cost / 1M Tokens
$3.00
$10.00
Claude 3.7 Sonnet is 3.3x cheaper
Output Cost / 1M Tokens
$15.00
$50.00
Claude 3.7 Sonnet (70.0% lower)
Prompt Cache Read / 1M
$0.300
$1.000
Claude 3.7 Sonnet is 3.3x cheaper
Prompt Cache Write / 1M
$3.75
$12.50
Claude 3.7 Sonnet is 3.3x cheaper
Context Window (Max Output)
205k (64k out)
1,075k (128k out)
GPT-6 Astra (5.3x larger context)
Avg TTFT Response Latency
540ms
740ms
Claude 3.7 Sonnet (200ms faster)
Generation Speed (Throughput)
72 tok/s
74 tok/s
GPT-6 Astra (+2 tok/s faster)
SWE-bench Verified (Coding)
70.3%
75.7%
GPT-6 Astra (+5.4% lead)
GPQA Diamond (PhD STEM)
78.5%
96%
GPT-6 Astra (+17.5% lead)
MMLU-Pro (Multi-Discipline)
88%
91.2%
GPT-6 Astra (+3.2% lead)
MATH-500 (Quantitative Logic)
96.2%
98%
GPT-6 Astra (+1.8% lead)
Inference Value Score (IVR)
54.3 / 100
47.6 / 100
Claude 3.7 Sonnet (+6.7 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Which is cheaper: Claude 3.7 Sonnet or GPT-6 Astra?
Claude 3.7 Sonnet is cheaper at $3.00/1M input tokens ($15.00/1M output) compared to $10.00/1M input ($50.00/1M output) for GPT-6 Astra.
Which model has lower TTFT latency and higher tok/s throughput: Claude 3.7 Sonnet or GPT-6 Astra?
Claude 3.7 Sonnet delivers faster first-token latency at 540ms TTFT (72 tok/s throughput) compared to 740ms TTFT (74 tok/s) for GPT-6 Astra.
How do Claude 3.7 Sonnet and GPT-6 Astra compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 3.7 Sonnet scores 70.3% versus 75.7% for GPT-6 Astra. On GPQA Diamond graduate-level STEM reasoning, Claude 3.7 Sonnet scores 78.5% versus 96% for GPT-6 Astra (and 96.2% vs 98% 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 GPT-6 Astra?
Choose GPT-6 Astra (OpenAI) for high-autonomy flagship reasoning model engineered for end-to-end computer and browser use, advanced scientific research, and complex multi-turn software engineering — offering a 1,075k context window, 740ms TTFT, and $10.00/1M input pricing ($1.000/1M cached reads).
