Which model is better: Claude 3.5 Haiku or GPT-6 Astra?
Claude 3.5 Haiku is 92.0% cheaper for input tokens ($0.80 vs. $10.00 per 1M tokens) and $4.00 vs. $50.00 for output tokens (12.5x cost advantage). In terms of operational performance, Claude 3.5 Haiku delivers lower response latency at 190ms TTFT (550ms faster than GPT-6 Astra) with 130 vs. 74 tok/s throughput. GPT-6 Astra leads coding evaluations at 75.7% SWE-bench Verified vs. 40.6% for Claude 3.5 Haiku and 96.0% vs. 41.6% 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 3.5 Haiku
GPT-6 Astra
Net Delta / Advantage
Input Cost / 1M Tokens
$0.80
$10.00
Claude 3.5 Haiku is 12.5x cheaper
Output Cost / 1M Tokens
$4.00
$50.00
Claude 3.5 Haiku (92.0% lower)
Prompt Cache Read / 1M
$0.080
$1.000
Claude 3.5 Haiku is 12.5x cheaper
Prompt Cache Write / 1M
$1.00
$12.50
Claude 3.5 Haiku is 12.5x cheaper
Context Window (Max Output)
205k (8k out)
1,075k (128k out)
GPT-6 Astra (5.3x larger context)
Avg TTFT Response Latency
190ms
740ms
Claude 3.5 Haiku (550ms faster)
Generation Speed (Throughput)
130 tok/s
74 tok/s
Claude 3.5 Haiku (+56 tok/s faster)
SWE-bench Verified (Coding)
40.6%
75.7%
GPT-6 Astra (+35.1% lead)
GPQA Diamond (PhD STEM)
41.6%
96%
GPT-6 Astra (+54.4% lead)
MMLU-Pro (Multi-Discipline)
71%
91.2%
GPT-6 Astra (+20.2% lead)
MATH-500 (Quantitative Logic)
69.4%
98%
GPT-6 Astra (+28.6% lead)
Inference Value Score (IVR)
52.4 / 100
47.6 / 100
Claude 3.5 Haiku (+4.8 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 3.5 Haiku or GPT-6 Astra?
Claude 3.5 Haiku is cheaper at $0.80/1M input tokens ($4.00/1M 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 3.5 Haiku or GPT-6 Astra?
Claude 3.5 Haiku delivers faster first-token latency at 190ms TTFT (130 tok/s throughput) compared to 740ms TTFT (74 tok/s) for GPT-6 Astra.
How do Claude 3.5 Haiku and GPT-6 Astra compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 3.5 Haiku scores 40.6% versus 75.7% for GPT-6 Astra. On GPQA Diamond graduate-level STEM reasoning, Claude 3.5 Haiku scores 41.6% versus 96% for GPT-6 Astra (and 69.4% vs 98% on MATH-500).
When should you choose Claude 3.5 Haiku?
Choose Claude 3.5 Haiku (Anthropic) for rapid customer-facing chat, sub-agent routing, and real-time code autocomplete — offering a 204k context window, 190ms TTFT, and $0.80/1M input pricing ($0.080/1M 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).
