o3 vs Claude 3.5 Haiku
Compare pricing, context windows, and strengths for o3 by OpenAI and Claude 3.5 Haiku by Anthropic - and see how to put either to work in Appaca.
o3
A powerful reasoning model excelling at complex, multi-step tasks across math, science, coding, and visual reasoning; succeeded by GPT-5.
View o3Claude 3.5 Haiku
A fast, affordable model matching Claude 3 Opus on many tasks while delivering major improvements in coding, accuracy, and tool use.
View Claude 3.5 Haikuo3 vs Claude 3.5 Haiku at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | o3 | Claude 3.5 Haiku |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model type | Text | Text |
| Context window | 200K tokens | 200K tokens |
| Input price | $2 / 1M tokens | $0.8 / 1M tokens |
| Output price | $8 / 1M tokens | $4 / 1M tokens |
| Status | Current | Superseded by Claude 4.5 Haiku |
How o3 and Claude 3.5 Haiku differ
What the numbers mean in practice when choosing between o3 and Claude 3.5 Haiku.
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Claude 3.5 Haiku is 60% cheaper on input tokens ($0.8 vs $2 per million), which adds up quickly in document-heavy workloads.
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Claude 3.5 Haiku is 50% cheaper on output tokens ($4 vs $8 per million) - the bigger factor for tools that generate long documents.
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Both models offer the same 200K tokens context window.
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Claude 3.5 Haiku has been superseded by Claude 4.5 Haiku - for new builds, consider the newer model first.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
o3
1. Advanced reasoning capability
- Designed for multi-step thinking across text, code, and visual inputs.
- Excels at math, science, logic puzzles, and complex analytical workflows.
2. Strong performance across domains
- Highly capable in technical writing, data analysis, and structured problem-solving.
- Useful for research, engineering tasks, and intricate instruction-following.
3. Visual reasoning support
- Accepts image inputs, enabling tasks such as diagram analysis, chart interpretation, and visual logic assessments.
4. High output capacity
- Up to 100,000 output tokens, supporting long-form content, technical breakdowns, and multi-part solutions.
5. Excellent instruction following
- Produces detailed, step-by-step responses for tasks requiring precision and clarity.
- Ideal for educational explanations, system design reasoning, and code walkthroughs.
6. Large 200K context window
- Handles long documents, multi-file reasoning, or extended conversations with minimal loss of context.
7. Broad API support
- Works with Chat Completions, Responses, Realtime, Assistants, Batch, Embeddings, Image Generation, and more.
- Supports streaming and function calling for advanced workflows.
8. Positioned as a legacy reasoning model
- Remains extremely capable but formally succeeded by GPT-5, which offers stronger reasoning and performance.
Claude 3.5 Haiku
1. Intelligence & Benchmark Performance
- Matches Claude 3 Opus (previous largest model) on many intelligence tasks.
- Surpasses Claude 3 Opus on multiple evaluations despite being a smaller, faster model.
- Major improvements across every skill category vs previous Haiku.
2. Coding Strength
Scores 40.6% on SWE-bench Verified, outperforming:
- Claude 3.5 Sonnet (original version)
- GPT-4o
- Many agent-driven systems
Excellent for engineering assistants, agent coding tasks, and bug fixing.
3. Speed & Latency
- Same speed class as Claude 3 Haiku (ultra-fast).
- Ideal for real-time interactions, high request volumes, and UI responsiveness.
4. Tool Use & Instruction Following
- Better at following instructions than previous Haiku.
- Stronger at tool use accuracy, making it reliable for agents and workflows.
5. Best Use Cases
- High-volume, low-latency tasks
- User-facing products
- Sub-agent tasks in larger workflows
- Processing large structured datasets (pricing, inventory, purchase history)
- Rapid content or code generation where speed matters
Use o3 or Claude 3.5 Haiku - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by o3 or Claude 3.5 Haiku - connected to your real data and ready for your whole team. No code, no deployment.
Describe it, and it's built
Tell the Appaca agent the internal tool you need and it builds a working app powered by o3 or Claude 3.5 Haiku. No code, no API keys, no deployment.
Switch models without rebuilding
Start on o3, test the same tool on Claude 3.5 Haiku, and keep whichever performs better - the rest of your app stays exactly as it is.
Automated for the whole team
Schedule tools to run on autopilot - daily digests, weekly reports, real-time triggers - and share them with your whole team from one workspace.
Describe it, and it's built
Tell the Appaca agent what your team needs and it builds a working app powered by o3 or Claude 3.5 Haiku - connected to the tools you already use.
Related comparisons
See how o3 and Claude 3.5 Haiku stack up against other models in the directory.
FAQs
Claude 3.5 Haiku is generally cheaper: $0.8 input / $4 output per million tokens, versus $2 / $8 for o3. Actual cost depends on how many tokens your workload reads and writes.
They are equal: both o3 and Claude 3.5 Haiku support a 200K tokens context window.
It depends on the job. Compare the pricing, context window, and strengths above against your workload - and remember the choice isn't permanent. In Appaca you can build a tool on o3, test the same tool on Claude 3.5 Haiku, and switch at any time without rebuilding anything.
Yes. Appaca is a no-code AI workspace: describe the internal tool your team needs and the Appaca agent builds it as a working app powered by o3, Claude 3.5 Haiku, or any other model in the directory - with a built-in database, team access, and integrations. No API keys to wire up and nothing to deploy.
Build AI tools with o3 or Claude 3.5 Haiku
Describe the tool your team needs and get a working app powered by the model you choose - with a built-in database, team access, and integrations. No code, no deployment.