Claude 3.5 Haiku
Anthropic • text+image->text
Context Window200K
Knowledge CutoffNov 4, 2024
Claude 3.5 Haiku vs GPT-4o-mini
GPT-4o mini for OpenAI ecosystem integration, Claude 3.5 Haiku for Anthropic reliability in fast high-volume tasks.
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GPT-4o-mini
OpenAI • text+image+file->text
Context Window128K
Knowledge CutoffJul 18, 2024
Editorial Verdict
GPT-4o mini is the higher-capability mini model; Claude 3.5 Haiku is the ultra-fast budget option.
GPT-4o mini significantly outperforms Claude 3.5 Haiku on reasoning and coding benchmarks while maintaining competitive cost and speed. Claude 3.5 Haiku is the fastest and cheapest of the two. For capability, GPT-4o mini wins. For ultra-fast simple extraction at lowest cost, Claude 3.5 Haiku wins.
Claude 3.5 Haiku
- Significantly higher capability on reasoning and coding benchmarks
- 128K context window — 4x larger than Haiku's 32K
- More capable at complex multi-step tasks despite being a small model
Best for: Complex mini tasks requiring strong capability within a small model
GPT-4o-mini
- Fastest inference of any capable small model
- Lowest cost per token for simple extraction tasks
- Fast for real-time extraction and classification applications
Best for: Ultra-fast simple extraction and classification at lowest cost
Pricing sourced from OpenRouter — updates as their catalog changes.
Pricing Comparison
All values pull from OpenRouter and update as their catalog changes.
| Metric | Claude 3.5 Haiku | GPT-4o-mini | Winner |
|---|---|---|---|
| Input (per 1M tokens) | $0.80 | $0.15 | 🏆 GPT-4o-mini |
| Output (per 1M tokens) | $4.00 | $0.60 | 🏆 GPT-4o-mini |
| Request fee | N/A | N/A | N/A |
| Image fee | N/A | N/A | N/A |
Cost Estimator
Estimate monthly billing using real OpenRouter prices.
Claude 3.5 Haiku Total
$88GPT-4o-mini Total
$14.25Estimated Monthly Savings: $73.75 with GPT-4o-mini
Capability Signals
Scores are directional estimates from model metadata — not official benchmark results.
Claude 3.5 HaikuMMLU Signal (Reasoning)GPT-4o-mini
69%
69%
Claude 3.5 HaikuHumanEval Signal (Coding)GPT-4o-mini
86%
76%
Claude 3.5 HaikuAgentic Tooling SignalGPT-4o-mini
84%
84%
Claude 3.5 HaikuMultimodal SignalGPT-4o-mini
78%
78%
Capabilities Matrix
Feature highlights for architecture and production fit.
Claude 3.5 Haiku Strengths
- Supports image inputs for multimodal analysis workflows.
- Strong tool-calling and structured response support.
- Large context window for long documents and codebases.
GPT-4o-mini Strengths
- Supports image inputs for multimodal analysis workflows.
- Strong tool-calling and structured response support.
- Balanced general-purpose profile for chat, extraction, and automation tasks.
API Implementation
Quick start snippets for each provider style.
Anthropic (Python)
import anthropic
client = anthropic.Anthropic()
message = client.messages.create(
model="anthropic/claude-3.5-haiku",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello"}]
)
print(message.content)OpenAI (Python)
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="openai/gpt-4o-mini",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Choose Claude 3.5 Haiku when...
- Your application includes visual reasoning and image understanding tasks.
- You process large documents or code repositories in a single prompt.
- You rely on function calling, tool chaining, and structured output contracts.
Choose GPT-4o-mini when...
- Your application includes visual reasoning and image understanding tasks.
- You rely on function calling, tool chaining, and structured output contracts.
- You want a balanced default for mixed chat and workflow automation workloads.
Frequently Asked Questions
Practical checks before selecting a production model.
Is Claude 3.5 Haiku better than GPT-4o mini?
It depends on the workload. Claude 3.5 Haiku and GPT-4o mini differ in pricing, context window, and capability mix — see the side-by-side table above for the breakdown.
What's the price difference between Claude 3.5 Haiku and GPT-4o mini?
Claude 3.5 Haiku: $0.80 per 1M input tokens. GPT-4o mini: $0.15 per 1M input tokens. Output token pricing typically runs 2-5x higher.
Which model is better for coding?
Coding preference depends on your stack and tool-calling needs. Compare the coding signal row, test with your repository tasks, and validate latency in your target region.
Which model is cheaper at scale?
Input and output token pricing can diverge by workload profile. Use the estimator with your monthly request count and token mix to get a realistic cost difference.
Are these official benchmark numbers?
Pricing is live from OpenRouter. Benchmark rows are ModelsAtlas metadata-based signals and should be treated as directional guidance, not official leaderboard scores.
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