Claude Haiku 4.5 vs Claude Opus 4.6 for Writing

Winner: Claude Opus 4.6. In our Writing tests Opus scores 4.0 vs Claude Haiku 4.5's 3.5 (a 0.5-point advantage). Opus delivers stronger creative ideation (creative_problem_solving 5 vs 4) while matching Haiku on constrained rewriting (both 3). Opus also has far stronger safety_calibration (5 vs 2), which matters for publishable content and moderation-sensitive copy. Haiku 4.5 is the cost-efficient alternative — input/output cost per mTok of 1/5 vs Opus’s 5/25 — but it trails Opus on the core ideation and safety dimensions important to high-quality writing.

anthropic

Claude Haiku 4.5

Overall
4.33/5Strong

Benchmark Scores

Faithfulness
5/5
Long Context
5/5
Multilingual
5/5
Tool Calling
5/5
Classification
4/5
Agentic Planning
5/5
Structured Output
4/5
Safety Calibration
2/5
Strategic Analysis
5/5
Persona Consistency
5/5
Constrained Rewriting
3/5
Creative Problem Solving
4/5

External Benchmarks

SWE-bench Verified
N/A
MATH Level 5
N/A
AIME 2025
N/A

Pricing

Input

$1.00/MTok

Output

$5.00/MTok

Context Window200K

modelpicker.net

anthropic

Claude Opus 4.6

Overall
4.58/5Strong

Benchmark Scores

Faithfulness
5/5
Long Context
5/5
Multilingual
5/5
Tool Calling
5/5
Classification
3/5
Agentic Planning
5/5
Structured Output
4/5
Safety Calibration
5/5
Strategic Analysis
5/5
Persona Consistency
5/5
Constrained Rewriting
3/5
Creative Problem Solving
5/5

External Benchmarks

SWE-bench Verified
78.7%
MATH Level 5
N/A
AIME 2025
94.4%

Pricing

Input

$5.00/MTok

Output

$25.00/MTok

Context Window1000K

modelpicker.net

Task Analysis

What Writing demands: fast, original ideation (headlines, hooks, story beats), reliable constrained rewriting (short-form edits and character-limited copy), persona and tone consistency, long-context memory for extended briefs, structured outputs for CMS-ready copy, and safety calibration for publishable content. Since no external benchmark applies, our internal task metrics are primary. On those metrics: Opus leads on creative_problem_solving (5 vs 4), a direct proxy for ideation quality; constrained_rewriting is tied at 3, indicating similar performance on tight edits; both models tie on long_context (5), persona_consistency (5), structured_output (4) and faithfulness (5), so they handle extended briefs, tone, and factual adherence equivalently in our testing. The major differentiator is safety_calibration (Opus 5 vs Haiku 2) and creative ideation, which together explain Opus’s higher Writing score and rank (taskRank 6 vs Haiku’s 29). Cost and latency trade-offs also matter: Haiku is designed to be faster and much cheaper (input_cost 1/output_cost 5 vs Opus 5/25).

Practical Examples

  1. High-stakes marketing campaign (winner: Opus 4.6). Opus scores 5 on creative_problem_solving vs Haiku’s 4 — in our tests Opus produces more original, multi-angle campaign concepts and safer copy variants suitable for publication (safety_calibration 5 vs 2). 2) Bulk content production with tight budget (winner: Haiku 4.5). Haiku’s input/output costs are 1/5 per mTok vs Opus’s 5/25, making it ~5x cheaper per token in our pricing units; it still ties on long_context (5) and structured_output (4), so it's efficient for templated blog posts and CMS-ready drafts. 3) Short-form constrained rewrites (tie). Both models score 3 on constrained_rewriting, so expect similar results for strict character-limited ad copy — neither is exceptional at extreme compression in our tests. 4) Tone-heavy brand voice and long briefs (either). Both models score 5 on persona_consistency and 5 on long_context, so both maintain voice across long documents in our testing; choose Opus when you need stronger ideation and safety, Haiku when cost per token matters.

Bottom Line

For Writing, choose Claude Haiku 4.5 if you need lower-cost, fast bulk content or templated CMS output (input_cost_per_mtok 1, output_cost_per_mtok 5) and can tolerate slightly weaker ideation and safety. Choose Claude Opus 4.6 if you need stronger ideation and safer, publish-ready copy (creative_problem_solving 5 vs 4, safety_calibration 5 vs 2) and can accept higher per-token costs (input_cost_per_mtok 5, output_cost_per_mtok 25).

How We Test

We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.

Frequently Asked Questions