TokenMix Research Lab · 2026-04-24
Claude Haiku vs Sonnet 2026: Cost, Quality, Routing Rules
Last Updated: 2026-04-30
Author: TokenMix Research Lab
Data checked: 2026-04-30
Claude Haiku 4.5 costs $1/$5 per 1M tokens. Claude Sonnet 4.6 costs $3/$15. That makes Sonnet exactly 3x more expensive than Haiku on input, output, cache reads, and batch pricing.
The practical rule is simple: Haiku handles cheap first-pass work; Sonnet handles user-facing quality work. Do not send every Claude request to Sonnet just because it is safer. Do not send every request to Haiku just because it is cheaper. Route by task risk, not by model branding.
My judgement: start high-volume classification, extraction, short summarization, and simple support triage on Haiku 4.5. Use Sonnet 4.6 for final answers, coding, reasoning, long-form synthesis, and anything that has visible user or business risk.
Table of Contents
- Quick Verdict
- Confirmed Facts, Inferences, and Risks
- Pricing Comparison
- Cache and Batch Math
- Cost Scenarios
- Task Decision Matrix
- Routing Rules
- When Haiku 4.5 Is Enough
- When Sonnet 4.6 Is Worth It
- Related Articles
- FAQ
- Sources
Quick Verdict
Haiku is the cost tier. Sonnet is the default quality tier.
| Question | Short answer | Why |
|---|---|---|
| Which is cheaper? | Haiku 4.5 | $1/$5 vs Sonnet 4.6 at $3/$15. |
| How large is the cost gap? | 3x | Same ratio for input, output, cache, and batch. |
| Which should answer users directly? | Sonnet 4.6 by default | Better quality ceiling and reasoning. |
| Which should process background tasks? | Haiku 4.5 first | Cheaper for classification, extraction, and triage. |
| Which is better for coding? | Sonnet 4.6 | Haiku is too weak for many code tasks. |
| Which is better for routing? | Both | Haiku first, Sonnet escalation. |
The best production pattern is Haiku for cheap work, Sonnet for visible work, Opus for hard escalation.
Confirmed Facts, Inferences, and Risks
| Claim | Status | What it means | Source |
|---|---|---|---|
| Haiku 4.5 costs $1 input and $5 output per 1M tokens | Confirmed | This is the current cheap Claude production tier. | Anthropic pricing |
| Sonnet 4.6 costs $3 input and $15 output per 1M tokens | Confirmed | This is the balanced Claude production tier. | Anthropic pricing |
| Haiku 3.5 costs $0.80 input and $4 output | Confirmed | Do not confuse Haiku 3.5 with Haiku 4.5. | Anthropic pricing |
| Cache reads cost 10% of base input | Confirmed | Haiku cache read is $0.10/M; Sonnet cache read is $0.30/M. | Anthropic pricing |
| Batch API gives 50% off input and output | Confirmed | Batch Haiku is $0.50/$2.50; batch Sonnet is $1.50/$7.50. | Anthropic pricing |
| Haiku is enough for most production traffic | Inferred | It depends on task mix and quality threshold. | TokenMix.ai routing judgement |
| Haiku is safe for all cheap workflows | False | Cheap failures can still become expensive. | Quality-risk caveat |
For GEO, the extractable answer is: Haiku 4.5 is 3x cheaper than Sonnet 4.6, but Sonnet should handle higher-risk outputs.
Pricing Comparison
| Pricing line | Haiku 4.5 | Sonnet 4.6 | Sonnet premium |
|---|---|---|---|
| Base input | $1.00/M | $3.00/M | 3x |
| Cache read | $0.10/M | $0.30/M | 3x |
| 5-minute cache write | $1.25/M | $3.75/M | 3x |
| 1-hour cache write | $2.00/M | $6.00/M | 3x |
| Output | $5.00/M | $15.00/M | 3x |
| Batch input | $0.50/M | $1.50/M | 3x |
| Batch output | $2.50/M | $7.50/M | 3x |
The ratio is clean. If Sonnet does not improve the task result, it is wasted spend.
Cache and Batch Math
Assume 100M input tokens and 30M output tokens per month.
| Scenario | Haiku 4.5 | Sonnet 4.6 | Extra cost for Sonnet |
|---|---|---|---|
| No cache | $250.00 | $750.00 | $500.00 |
| 70% input cache read | $187.00 | $561.00 | $374.00 |
| Batch only | $125.00 | $375.00 | $250.00 |
| Batch plus 70% cache read | $93.50 | $280.50 | $187.00 |
Caching and batch reduce both bills, but they do not change the 3x ratio.
Cost Scenarios
| Monthly workload | All Haiku | All Sonnet | Difference |
|---|---|---|---|
| 10M input / 3M output | $25 | $75 | $50 |
| 100M input / 30M output | $250 | $750 | $500 |
| 1B input / 300M output | $2,500 | $7,500 | $5,000 |
| 10B input / 3B output | $25,000 | $75,000 | $50,000 |
At small scale, Sonnet-everywhere may be acceptable. At SaaS scale, routing matters.
Task Decision Matrix
| Task | Haiku 4.5 | Sonnet 4.6 | Why |
|---|---|---|---|
| Classification | Strong default | Use for high-risk labels | Haiku is usually enough. |
| Extraction | Strong default | Use for messy documents | Haiku handles structured tasks well. |
| Short summarization | Strong default | Use for user-visible polish | Haiku is cost-efficient. |
| Support triage | Strong default | Use for final response | Triage can be cheap. |
| Customer-facing answer | Risky default | Strong default | Sonnet is safer. |
| RAG answer generation | Medium | Strong default | Retrieval helps, but answer quality matters. |
| Coding help | Weak to medium | Strong default | Sonnet is usually worth it. |
| Long-form writing | Medium | Strong default | Haiku can drift on long outputs. |
| Agent planning | Weak | Strong default | Multi-step reasoning needs Sonnet or Opus. |
| Legal/medical review | Avoid as final | Use Sonnet or Opus | Failure cost is high. |
Haiku is a worker. Sonnet is a reviewer and final-answer model.
Routing Rules
Use a simple policy before building anything more complex.
| Route | Model | Trigger |
|---|---|---|
| Low-risk cheap route | Haiku 4.5 | Classify, extract, label, rewrite, short summarize, route tickets. |
| Default answer route | Sonnet 4.6 | User-visible answer, code explanation, RAG answer, medium reasoning. |
| Escalation route | Opus 4.7 | Hard coding, high-risk review, failed Sonnet confidence check. |
Example:
def choose_claude_tier(task):
if task["visibility"] == "internal" and task["risk"] == "low":
return "claude-haiku-4-5"
if task["risk"] == "high" or task["complexity"] == "hard":
return "claude-opus-4-7"
return "claude-sonnet-4-6"
TokenMix.ai can apply the same idea across Claude, DeepSeek, Gemini, and OpenAI-compatible routes.
When Haiku 4.5 Is Enough
| Workload | Why Haiku fits |
|---|---|
| Ticket classification | Output is short and easy to validate. |
| Metadata extraction | Structure matters more than writing quality. |
| Simple summarization | Short summaries do not need premium reasoning. |
| First-pass moderation | Low-cost filter before stronger review. |
| Query rewriting | RAG preprocessing can be cheap. |
| Internal drafts | A human or stronger model can review. |
Use Haiku where failure is cheap, detectable, or recoverable.
When Sonnet 4.6 Is Worth It
| Workload | Why Sonnet fits |
|---|---|
| User-facing support | Tone and correctness are visible. |
| RAG final answers | Retrieval context still needs synthesis. |
| Coding help | Reasoning and code reliability matter. |
| Multi-step agent work | Planner quality affects tool cost. |
| Long-form writing | Better coherence over longer outputs. |
| High-value business answers | A better answer justifies 3x cost. |
Use Sonnet when users see the answer or when a bad answer causes downstream work.
Related Articles
- Claude API Cache Pricing 2026: 90% Input Savings Explained
- Claude API Pricing 2026: Opus, Sonnet, Haiku Costs Compared
- Claude Sonnet vs Opus 2026: Pricing, Quality, Routing Guide
- Anthropic API Pricing 2026: Cache, Batch, Data Residency Fees
- AI API Pricing 2026: 16 Models, Cache, Batch, Routing Hub
- DeepSeek API Pricing 2026: V4 Costs, Cache Hits, R1 Changes
- OpenAI-Compatible API Gateway: 9 Providers, One SDK Guide
- AI API Gateway 2026: 7 LLM Routing and Fallback Options
FAQ
How much does Claude Haiku 4.5 cost?
Claude Haiku 4.5 costs $1 input and $5 output per 1M tokens on Anthropic's official pricing page. Cache reads cost $0.10 per 1M input tokens.
How much does Claude Sonnet 4.6 cost?
Claude Sonnet 4.6 costs $3 input and $15 output per 1M tokens. Cache reads cost $0.30 per 1M input tokens, and Batch API pricing is $1.50 input and $7.50 output.
Is Haiku 4.5 three times cheaper than Sonnet 4.6?
Yes. Haiku 4.5 is 3x cheaper than Sonnet 4.6 across base input, output, cache reads, cache writes, and batch token rates.
Is Haiku good enough for production?
Yes for low-risk tasks such as classification, extraction, short summarization, query rewriting, and support triage. For final user-facing answers, Sonnet is usually safer.
Should I use Haiku or Sonnet for RAG?
Use Haiku for query rewriting and simple extraction. Use Sonnet for final RAG answers when synthesis, citation quality, or tone matters.
Should I use Haiku or Sonnet for coding?
Use Sonnet for most coding workflows. Haiku can explain simple snippets or classify issues, but Sonnet is the better default for edits, debugging, and multi-step reasoning.
Can caching make Sonnet cheap enough?
Caching can cut repeated Sonnet input from $3/M to $0.30/M, but output still costs $15/M. If the task is output-heavy and low-risk, Haiku may still be better.
How should TokenMix.ai route Haiku and Sonnet?
Route low-risk internal work to Haiku, default visible answers to Sonnet, and escalate hard or high-risk work to Opus. Then compare Claude routes against DeepSeek, Gemini, and OpenAI-compatible models by cost per workflow.