Claude 3.5 Haiku vs GPT-4o mini
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Claude 3.5 Haiku by Anthropic and GPT-4o mini by OpenAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, GPT-4o mini holds a notable pricing advantage for token ingestion. On output generation, GPT-4o mini is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude 3.5 Haiku provides an expanded memory horizon with 200K tokens. In latency-sensitive production environments, GPT-4o mini leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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Claude 3.5 Haiku
Sub-Agent Speed DemonAnthropic's fastest model, delivering high intelligence at rapid execution speeds, matching the coding capabilities of previous-generation flagship models.
$0.80 / 1M
$4.00 / 1M
200K tokens
40.6%
GPT-4o mini
Compact UtilityOpenAI's compact, cost-efficient small model designed to replace GPT-3.5 Turbo across high-volume classification, extraction, and utility tasks.
$0.15 / 1M
$0.60 / 1M
128K tokens
24.5%
Key Differences at a Glance
- GPT-4o mini is 5.6x cheaper for API usage (input + output tokens combined).
- Claude 3.5 Haiku has a larger context window (200K vs 128K tokens).
- GPT-4o mini is faster at 140 tok/s vs 130 tok/s.
- Claude 3.5 Haiku leads on SWE-bench coding (40.6% vs 24.5%).
| Feature | Claude 3.5 Haiku | GPT-4o mini |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 36 | 30 |
Provider | Anthropic | OpenAI |
Input Price Cost per million input tokens | $0.80 / 1M | $0.15 / 1M |
Output Price Cost per million output tokens | $4.00 / 1M | $0.60 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.62 / 1M | $0.14 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 8K | 16K |
Throughput Speed Tokens generated per second | 130 tok/s | 140 tok/s |
SWE-bench Verified Real-world software engineering | 40.6% | 24.5% |
GPQA Diamond Graduate-level reasoning | 41.6% | 40.2% |
Cached Input Price Prompt caching discount per 1M tokens | $0.08 / 1M | $0.07 / 1M |
Who Wins Where?
At-a-glance decision frameworkEmpirical Head-to-Head Benchmark Scores
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latency & Response Time
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Real-Time Interactive Token Cost Simulator
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Claude 3.5 Haiku · Strengths & Key Advantages
- High throughput of 130 tokens per second for real-time applications
- Generous 200K token context window despite compact size
- Solid software engineering performance (40.6% SWE-bench Verified)
- Accurate tool calling and strict schema output generation
Considerations & Trade-offs
- Higher output price ($4.00/1M) compared to competitor lightweight models like Gemini Flash
- Lower deep STEM reasoning than full Sonnet or o-series models
GPT-4o mini · Strengths & Key Advantages
- Economical pricing ($0.15 in / $0.60 out per 1M tokens)
- Full vision multimodal support at low cost
- High output token limit (16K tokens)
- Consistent function calling and JSON output reliability
Considerations & Trade-offs
- Limited reasoning for complex software architecture
- Slightly higher pricing than Gemini 2.0 Flash ($0.15 vs $0.10)
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude 3.5 Haiku | GPT-4o mini |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.90 | $0.16 |
Output Tokens / Task Tokens generated per task | 45K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Technical Specifications
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude 3.5 Haiku | GPT-4o mini |
|---|---|---|
| Official API Model ID (SDK) | claude-3-5-haiku-20241101 | gpt-4o-mini |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-11 | 2024-07 |
| Knowledge Cutoff | July 2024 | October 2023 |
| Architecture | Optimized Lightweight Transformer | Small Multimodal Dense |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($0.15/1M in) across full 128K window |
| Prompt Cache Policy & TTL | $0.08/1M cached read (90% off); 5-min default & 1-hour extended TTL | Automatic prefix caching at $0.075/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Native Web Search Citations + Code Execution Tool + MCP Connectors | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated | OpenAI Preparedness Framework Audited & System Card Published |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text, vision |
| Output Modalities | text | text |
Claude 3.5 Haiku vs GPT-4o mini: Quick Answers
Which is more intelligent, Claude 3.5 Haiku or GPT-4o mini?
Claude 3.5 Haiku is more intelligent. It scores 36 compared with 30 on the composite Intelligence Index.
Which model is faster?
GPT-4o mini is faster, generating 140 tokens per second compared with 130 tokens per second.
Which model is cheaper to run?
GPT-4o mini is cheaper at $0.14 per 1M tokens blended, compared with $0.62 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-4o mini has lower latency, with a time to first token of 0.31s compared with 0.38s.
Which model has a larger context window?
Claude 3.5 Haiku has a larger context window, supporting 200K tokens compared with 128K tokens.
Verdict
Verdict & Model Selection Recommendation: Choose Claude 3.5 Haiku if your priority is Rapid customer support chatbots, data extraction agents, and interactive tool-using loops. Its performance in demanding tasks justifies its operational token cost. Choose GPT-4o mini if your workflow prioritizes Data extraction, customer support routing, and lightweight web scraping. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Frequently asked questions
How does Claude 3.5 Haiku compare to GPT-4o mini in API token pricing and cost per token?+
Claude 3.5 Haiku costs $0.80 per 1M input tokens and $4.00 per 1M output tokens, whereas GPT-4o mini costs $0.15 input and $0.60 output. Overall, GPT-4o mini is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Claude 3.5 Haiku or GPT-4o mini?+
Claude 3.5 Haiku supports a context window of 200K tokens (~150k words), while GPT-4o mini supports 128K tokens (~96k words). Therefore, Claude 3.5 Haiku can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Claude 3.5 Haiku or GPT-4o mini?+
Claude 3.5 Haiku scores 40.6% on SWE-bench Verified while GPT-4o mini scores 24.5%. For autonomous software engineering and multi-file debugging, Claude 3.5 Haiku holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Claude 3.5 Haiku and GPT-4o mini?+
Claude 3.5 Haiku is optimized for low-latency direct generation. In contrast, GPT-4o mini focuses on standard fast inference.
How does inference speed (tokens per second) compare between Claude 3.5 Haiku and GPT-4o mini?+
Claude 3.5 Haiku generates approximately 130 tokens per second, while GPT-4o mini delivers 140 tokens per second. In latency-sensitive production environments, GPT-4o mini provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Claude 3.5 Haiku and GPT-4o mini to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-4o mini to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude 3.5 Haiku. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs