Comparing the two dominant lightweight frontier models. Analyze token pricing disparities, SWE-bench coding benchmarks, prompt caching economics, and inference speed for high-volume customer workflows.
Calculate monthly bills across Claude 3.5 Haiku and GPT-4o-mini for high-throughput automated classification.
Evaluating architecture specifications, benchmark rates, throughput latency, and pricing tiers.
| Dimension | Claude 3.5 Haiku | GPT-4o-mini | Key Takeaway / Advantage |
|---|---|---|---|
| Input Cost / 1M Tokens | $0.80 | $0.15 | GPT-4o-mini (5.3x cheaper) |
| Output Cost / 1M Tokens | $4.00 | $0.60 | GPT-4o-mini (6.7x cheaper) |
| SWE-bench Verified Coding | 40.6% | 20.2% | Claude 3.5 Haiku (2x higher accuracy) |
| Context Window | 200,000 tokens | 128,000 tokens | Claude 3.5 Haiku (+56%) |
| Prompt Caching Hit Rate | $0.08 / 1M (90% discount) | $0.075 / 1M (50% discount) | Tie (~$0.08/M) |
| Structured Outputs | Tool calling / JSON formatting | Guaranteed strict JSON Schema | GPT-4o-mini |
| Fine-Tuning Availability | Not available on Haiku | Native self-service Fine-Tuning API | GPT-4o-mini |
Anthropic made a deliberate design decision with Claude 3.5 Haiku: instead of building an ultra-cheap toy model, they built a compact powerhouse. Scoring 40.6% on SWE-bench Verified, Claude 3.5 Haiku is actually more intelligent at coding and agentic reasoning than Anthropic's previous flagship model, Claude 3 Opus. For fast coding auto-complete, lightweight agentic sub-tasks, and complex data parsing, Haiku delivers premium frontier intelligence at $0.80 in / $4.00 out.
However, for high-volume commodity LLM pipelines, GPT-4o-mini is an economic juggernaut. At $0.15 per million input tokens and $0.60 per million output tokens, GPT-4o-mini is roughly 6x cheaper than Haiku. For simple sentiment analysis, classification, intent detection, and summarization where 40.6% SWE-bench capability is unnecessary, GPT-4o-mini prevents budget blowout.
Evaluating real monthly unit economics across practical engineering architectures.
Filtering incoming social comments and support chat messages. GPT-4o-mini costs $85/month versus Claude 3.5 Haiku's $520/month, saving 84%.
Predicting multi-line code completions within developer IDEs. Claude 3.5 Haiku's 40.6% SWE-bench score produces fewer syntax errors and hallucinations.
Querying a static 100k token document repeatedly. Haiku's 90% caching discount ($0.08/M) matches GPT-4o-mini's cached rate ($0.075/M) while delivering double the reasoning accuracy.
import os
import anthropic
from openai import OpenAI
anthropic_client = anthropic.Anthropic()
openai_client = OpenAI()
def classify_text(text: str, model_type: str = "budget"):
"""Route between ultra-cheap (mini) and high-accuracy (haiku)."""
if model_type == "budget":
# GPT-4o-mini: $0.15 / M in
res = openai_client.chat.completions.create(
model="gpt-4o-mini",
messages=[{"role": "user", "content": f"Classify intent: {text}"}]
)
return res.choices[0].message.content
else:
# Claude 3.5 Haiku: $0.80 / M in (higher accuracy)
res = anthropic_client.messages.create(
model="claude-3-5-haiku-20241022",
max_tokens=1024,
messages=[{"role": "user", "content": f"Classify intent: {text}"}]
)
return res.content[0].textReal-world engineering trade-offs and hidden bill shock traps to watch out for.
Explore complementary benchmarks and financial modeling tools across the index.
Compare flagship models for complex programming tasks.
Detailed breakdown of GPT-4o, GPT-4o-mini, and Realtime audio.
Rankings of budget AI models under $1 per million tokens.
Simulate exact cache hit savings on long context windows.
Claude 3.5 Haiku was engineered for frontier intelligence in a small footprint. Scoring 40.6% on SWE-bench Verified (double GPT-4o-mini's 20.2%), Haiku surpasses previous flagship models like Claude 3 Opus.
GPT-4o-mini is $0.15/M input and $0.60/M output. Claude 3.5 Haiku is $0.80/M input and $4.00/M output, making GPT-4o-mini roughly 5.3x to 6.7x cheaper.
Claude 3.5 Haiku has a 200,000 token context window, compared to GPT-4o-mini's 128,000 tokens.
Yes! OpenAI offers self-service fine-tuning on GPT-4o-mini at $0.30/M input and $1.20/M output, plus nominal training costs.
Anthropic provides a 90% discount on cached inputs for Haiku ($0.08/M). OpenAI provides a 50% discount on cached inputs for GPT-4o-mini ($0.075/M). On cache hits, their input pricing is virtually identical.
GPT-4o-mini is recommended for high-volume classification and extraction because its 6x lower cost saves substantial money without compromising accuracy on basic tasks.