GPT-5.1 vs Claude 3.5 Haiku
Compare GPT-5.1 and Claude 3.5 Haiku. Find out which one is better for your use case.
Model Comparison
| Feature | GPT-5.1 | Claude 3.5 Haiku |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model Type | text | text |
| Context Window | 400,000 tokens | 200,000 tokens |
| Input Cost | $1.25 / 1M tokens | $0.80 / 1M tokens |
| Output Cost | $10.00 / 1M tokens | $4.00 / 1M tokens |
Strengths & Best Use Cases
GPT-5.1
- Best model for deep reasoning, coding, and agent workflows
- Supports configurable reasoning and minimal reasoning modes
- Multimodal: text + image (input & output)
- Excellent tool use chaining and long-form task handling
- Stronger accuracy, reliability, and instruction-following than GPT-5
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
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