OpenAI vs Anthropic: Real Cost Per Task (Not Just Per Token)
GPT-4.1 at $2/1M vs Claude Sonnet 4.6 at $3/1M. Real pricing math for every model, with per-task cost examples and routing strategies that cut 50%+ off your bill.
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The pricing landscape changed dramatically in 2026. OpenAI's GPT-4.1 undercuts Claude Sonnet on input tokens. Anthropic's Haiku 4.5 remains the cheapest capable model. Here's the real math.
Current Pricing (June 2026)
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OpenAI
| Model | Input (per 1M tokens) | Output (per 1M tokens) | Context | Best For |
|---|---|---|---|---|
| GPT-5.4 | $2.50 | $10.00 | 128K | Flagship reasoning |
| GPT-4.1 | $2.00 | $8.00 | 128K | Code, instruction-following |
| GPT-4.1 mini | $0.40 | $1.60 | 128K | Balanced performance |
| GPT-4.1 Nano | $0.10 | $0.40 | 128K | High-volume simple tasks |
| GPT-4o | $2.50 | $10.00 | 128K | Multimodal |
Discounts: 50% prompt caching on cache hits. 50% batch API discount.
Anthropic
| Model | Input (per 1M tokens) | Output (per 1M tokens) | Context | Best For |
|---|---|---|---|---|
| Claude Opus 4.7 | $5.00 | $25.00 | 200K | Complex analysis, research |
| Claude Sonnet 4.6 | $3.00 | $15.00 | 200K | Balanced, coding |
| Claude Haiku 4.5 | $1.00 | $5.00 | 200K | Fast, cheap, capable |
Discounts: 90% prompt caching on read hits. 25% batch API discount.
Head-to-Head: Same Tier
| Tier | OpenAI | Anthropic | Cheaper |
|---|---|---|---|
| Flagship | GPT-5.4: $2.50/$10 | Opus 4.7: $5/$25 | OpenAI (2x cheaper) |
| Mid-tier | GPT-4.1: $2/$8 | Sonnet 4.6: $3/$15 | OpenAI (input 33% cheaper, output 47% cheaper) |
| Budget | GPT-4.1 Nano: $0.10/$0.40 | Haiku 4.5: $1/$5 | OpenAI (10x cheaper input) |
On raw pricing, OpenAI wins every tier in 2026. But pricing alone doesn't determine your real cost.
Why Raw Pricing Is Misleading
1. Anthropic's Caching Is Better
Anthropic gives 90% discount on cached prompt reads. OpenAI gives 50%.
If 70% of your tokens hit cache (common in production):
- Sonnet 4.6 effective input: $0.30/1M (90% off on 70% of tokens)
- GPT-4.1 effective input: $1.30/1M (50% off on 70% of tokens)
With heavy caching, Anthropic becomes cheaper on input.
2. Opus 4.7's New Tokenizer
Opus 4.7 introduced a new tokenizer that produces ~35% more tokens for the same text compared to older models. Your effective cost per word is higher than the rate card suggests.
3. Output Tokens Dominate Your Bill
Most applications generate 3-5x more output tokens than input. At the output tier:
- GPT-4.1: $8/1M output
- Sonnet 4.6: $15/1M output
OpenAI is nearly 2x cheaper on output. If your app is output-heavy (code generation, long-form writing), this matters more than input pricing.
Real-World Cost Examples
Customer Support Bot (50K conversations/month)
Average: 400 input tokens, 200 output tokens per conversation.
| Provider | Model | Monthly Cost |
|---|---|---|
| OpenAI | GPT-4.1 Nano | $4.00 |
| OpenAI | GPT-4.1 mini | $24.00 |
| Anthropic | Haiku 4.5 | $70.00 |
| Anthropic | Sonnet 4.6 | $210.00 |
Winner: GPT-4.1 Nano — if quality is sufficient.
Code Generation (5K requests/month)
Average: 500 input tokens, 1,500 output tokens.
| Provider | Model | Monthly Cost |
|---|---|---|
| OpenAI | GPT-4.1 | $65.00 |
| Anthropic | Sonnet 4.6 | $120.00 |
| OpenAI | GPT-5.4 | $81.25 |
| Anthropic | Opus 4.7 | $200.00 |
Winner: GPT-4.1 — best code model per dollar.
RAG Pipeline (100K queries/month, heavy caching)
Average: 2,000 input tokens (80% cached), 500 output tokens.
| Provider | Model | Monthly Cost (with caching) |
|---|---|---|
| Anthropic | Sonnet 4.6 (90% cache discount) | $98.00 |
| OpenAI | GPT-4.1 (50% cache discount) | $120.00 |
| Anthropic | Haiku 4.5 (90% cache discount) | $35.00 |
| OpenAI | GPT-4.1 mini (50% cache discount) | $56.00 |
Winner: Anthropic — caching discount dominates for RAG.
The Real Strategy: Don't Pick One Provider
The best cost setup uses both. Route by task complexity:
import { CostLens } from 'costlens';
import OpenAI from 'openai';
const costlens = new CostLens({ apiKey: 'cl_...' });
const openai = costlens.wrapOpenAI(new OpenAI());
// CostLens routes simple prompts to cheaper models automatically
// Complex prompts stay on your default model
// You see exactly what each request costs in real-time
const resp openai.chat.completions.create({
model: 'gpt-4.1',
messages: [{ role: 'user', content: 'Summarize this document...' }],
});
// Terminal output: ✓ Routed to gpt-4.1-nano (saved $0.003)
Install in 30 seconds:
npm install costlens
No config needed — it tracks costs immediately and suggests cheaper routing opportunities.
Cost Optimization Checklist
- Audit your model usage — most teams use GPT-4 for tasks GPT-4.1 Nano handles fine
- Enable prompt caching — Anthropic's 90% discount is massive for repetitive prefixes
- Use batch API for non-realtime work — 50% off on OpenAI, 25% off on Anthropic
- Route by complexity — not every request needs your most expensive model
- Track actual spend — pricing pages show rates, not your real bill with retries and long contexts
Bottom Line
Raw pricing winner: OpenAI (cheaper at every tier in 2026)
With heavy caching: Anthropic (90% cache discount beats OpenAI's 50%)
For code generation: GPT-4.1 ($2/$8) — best instruction-following per dollar
For high-volume simple tasks: GPT-4.1 Nano ($0.10/$0.40) — unbeatable
For long-context RAG: Haiku 4.5 with caching — cheapest capable option
Best overall strategy: Use both. Route intelligently. Track everything.
Prices sourced from OpenAI API pricing and Anthropic pricing. Last updated June 2026.
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