The pricing difference between Claude Haiku 4.5 and GPT-4o-mini is significant. GPT-4o-mini costs $0.15 per million input tokens. Claude Haiku 4.5 costs $1.00 — 6.7× more. On output, the gap is 8.3×: $0.60 vs $5.00 per million tokens.
If cost were the only variable, this would be a short article. But Haiku 4.5 generates responses 53% faster than GPT-4o-mini, has a 200K vs 128K context window, and scores 2.4× higher on Artificial Analysis's composite intelligence index.
This comparison gives you the data to decide which model belongs where in your production stack.
Key Takeaways
- GPT-4o-mini: $0.15/$0.60 per 1M tokens — 6.7× cheaper on input than Claude Haiku 4.5 (pricepertoken.com, 2026)
- Claude Haiku 4.5: 92 tokens/sec output speed vs GPT-4o-mini's 60 tokens/sec — 53% faster streaming (Artificial Analysis, live 2026)
- Claude Haiku 4.5 Artificial Analysis Intelligence Index: 31/100 vs GPT-4o-mini: 13/100 — Haiku scores 2.4× higher
- Claude Haiku 4.5 SWE-bench Verified: 73.3% — making it "one of the world's best coding models" at the budget tier (Anthropic, 2025)
This post is part of our LLM Model Comparison Guide 2026.
The Core Numbers Side by Side
Budget models are for high-volume workloads where cost compounds fast. These are the numbers that determine which bill you pay at the end of the month.
| Metric | Claude Haiku 4.5 | GPT-4o-mini |
|---|---|---|
| Input price ($/1M tokens) | $1.00 | $0.15 |
| Output price ($/1M tokens) | $5.00 | $0.60 |
| Batch input price ($/1M tokens) | $0.50 | $0.075 |
| Context window | 200K tokens | 128K tokens |
| Output speed (tokens/sec) | 92.1 | 60.2 |
| TTFT (P50) | 0.80 seconds | 1.24 seconds |
| Intelligence Index (Artificial Analysis) | 31/100 | 13/100 |
| SWE-bench Verified | 73.3% | — |
Sources: Anthropic Pricing Docs + Artificial Analysis, live June 2026.
The 6.7× price gap is real. So are the capability differences. The decision comes down to which variable matters most for your specific workload.
Citation capsule: In 2026, Claude Haiku 4.5 achieves an Artificial Analysis Intelligence Index score of 31/100 vs GPT-4o-mini's 13/100 — a 2.4× quality advantage — while generating responses at 92.1 tokens/second vs GPT-4o-mini's 60.2 tokens/second (Artificial Analysis, live data, June 2026). The tradeoff: Haiku 4.5 costs 6.7× more on input and 8.3× more on output.
When GPT-4o-mini Wins
1. Pure volume workloads where quality is already sufficient
If you're running 10 million simple classification calls per month and GPT-4o-mini is already achieving your quality threshold, paying 6.7× more for Haiku buys you nothing. For FAQ retrieval, simple extraction, content moderation, and short summaries, GPT-4o-mini at $0.15/M input is the right call.
2. Batch async workloads
GPT-4o-mini batch pricing: $0.075/M input — effectively free for high-volume async jobs. Document processing, bulk tagging, nightly analytics: GPT-4o-mini in batch mode is hard to beat.
3. Simple structured output (JSON schemas)
OpenAI's structured outputs mode produces reliable JSON adherence. For strict schema output at high volume, GPT-4o-mini + structured outputs is a clean, cost-effective combination.
When Claude Haiku 4.5 Wins
1. Streaming chat where response speed matters to users
Claude Haiku 4.5 outputs at 92.1 tokens/second vs GPT-4o-mini's 60.2. For a 200-token response, that's 2.2 seconds vs 3.3 seconds of streaming. At 0.8s TTFT vs 1.24s, users see the first word 55% sooner. In a chat UX, this is the difference between feeling "instant" and feeling "laggy."
2. Code generation and software engineering tasks
Anthropic claims Haiku 4.5 is "one of the world's best coding models" — and the SWE-bench Verified score of 73.3% backs it up. GPT-4o-mini has no published SWE-bench score. For code completion, debugging, code review, and agent-based software tasks, Haiku 4.5 is the clear choice at the budget tier.
3. Long-document RAG pipelines
Haiku 4.5's 200K context window vs GPT-4o-mini's 128K is a hard cutoff for document-heavy workloads. If your system needs to load a 150K-token document into context, GPT-4o-mini simply can't do it. Haiku 4.5 can, and at 9× the context capacity, it reduces chunking complexity significantly.
4. Multi-document synthesis and complex reasoning
With a 2.4× intelligence index advantage, Haiku 4.5 handles multi-step reasoning, synthesis tasks, and complex instructions noticeably better than GPT-4o-mini. For customer support bots that handle nuanced queries, or assistants that reason across multiple documents, the quality gap justifies the price premium.
The Use-Case Decision Matrix
| Use Case | Recommendation | Reason |
|---|---|---|
| High-volume simple classification | GPT-4o-mini | 6.7× cheaper; quality sufficient |
| FAQ / short answer retrieval | GPT-4o-mini | Cost dominates at scale |
| Streaming chat (UX speed matters) | Claude Haiku 4.5 | 53% faster streaming |
| Long-document RAG (>128K context) | Claude Haiku 4.5 | Hard context limit on mini |
| Code generation / software agents | Claude Haiku 4.5 | 73.3% SWE-bench |
| Batch/async document processing | GPT-4o-mini | $0.075/M batch input |
| Multi-document synthesis | Claude Haiku 4.5 | 2.4× intelligence advantage |
| Simple structured JSON extraction | GPT-4o-mini | OpenAI structured outputs |
Frequently Asked Questions
Is Claude Haiku 4.5 worth 6.7x the price of GPT-4o-mini?
For specific workloads, yes. Code generation, streaming chat, and long-context RAG are the three clearest cases. For bulk classification, short extraction, and simple summarization, GPT-4o-mini delivers equivalent results at a fraction of the cost. The answer depends entirely on your specific task — don't make a blanket choice.
What's the monthly cost difference at 10M calls/month?
Assuming 500 input + 400 output tokens per call: GPT-4o-mini = $315/month. Claude Haiku 4.5 = $2,075/month. The $1,760/month difference is meaningful — but if Haiku 4.5's quality improvement reduces support tickets, agent retries, or churn, the ROI math may still favor it.
Does Claude Haiku support function calling and tool use?
Yes. Claude Haiku 4.5 supports tool use with the standard Anthropic tools API. GPT-4o-mini supports OpenAI's function calling API. Both are production-ready for agentic workflows, though Claude's tool use tends to be more reliable in multi-step agent chains based on practitioner reports.
Can I use both in the same app with routing?
Yes — and this is the recommended architecture. Route streaming chat, code tasks, and long-context queries to Haiku 4.5; route high-volume classification and batch processing to GPT-4o-mini. A proxy layer like Tokonomics handles routing, cost tracking, and budget alerts across both providers simultaneously.
The Bottom Line
GPT-4o-mini wins on price for any workload where quality is already sufficient. Claude Haiku 4.5 wins on speed, intelligence, and coding ability — and pays for itself on workloads where those factors improve outcomes.
The right answer is usually both: route by task type, track cost per feature, and let the data tell you which model is earning its price premium.
Read next: LLM Model Comparison Guide 2026 and The Cheapest LLM for Each Use Case.
Sources: Anthropic API Pricing | Artificial Analysis — Claude Haiku 4.5 | Artificial Analysis — GPT-4o-mini | Anthropic — Claude Haiku 4.5 Model Page
All sources retrieved June 2026.
About the authors: Written by the engineers behind Tokonomics. About → | Contact us →