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Claude Haiku 4.5 vs Claude Sonnet 5

Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

Claude Sonnet 5 scores higher, Claude Haiku 4.5 costs less — it depends on your workload.

Claude Sonnet 5 is ahead by 28.6 points overall, and Claude Haiku 4.5 lists 2.0× cheaper per blended million tokens. Whether 28.6 points is worth that depends on how much a wrong answer costs you. Claude Haiku 4.5 also leads on measured cost per point of capability, at $0.3893 per point.

anthropic

Claude Haiku 4.5

Blended / 1M
$2.00
Context
200K
Released
Oct 15, 2025
Overall score
46.0
reasoningtool callingimage inputfile inputprompt caching

anthropic

Claude Sonnet 5

Blended / 1M
$4.00
Context
1M
Released
Jun 30, 2026
Overall score
74.6
reasoningtool callingimage inputfile inputprompt caching

Specs and pricing

MetricClaude Haiku 4.5Claude Sonnet 5
LiveBench overall

Mean of the seven LiveBench category scores, 0–100. Higher is better.

46.074.6win
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.3893win$2.28
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$2.00win$4.00
Input price / 1M$1.00win$2.00
Output price / 1M$5.00win$10.00
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$0.100win$0.200
Context window200K1Mwin
Max output tokens64K128Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude Haiku 4.5 on top, Claude Sonnet 5 below, both out of 100.

Coding
48.1
82.2
Reasoning
61.7
88.7
Data analysis
59.3
71.7

What each one costs to run

Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.

WorkloadClaude Haiku 4.5Claude Sonnet 5
Support chatbot

1.2K in / 400 out × 200K requests

$575.20/mo$1,150/mo
RAG assistant

8K in / 600 out × 100K requests

$740.00/mo$1,480/mo
Coding agent

40K in / 4K out × 20K requests

$696.00/mo$1,392/mo
Document extraction

20K in / 1.5K out × 50K requests

$1,330/mo$2,660/mo
Bulk classification

500 in / 20 out × 5M requests

$2,550/mo$5,100/mo
Run these two through the cost calculator

Which should you pick?

You are running this at volume

Claude Haiku 4.5

Lowest measured cost per point of capability at $0.3893 per point — the gap compounds with every request.

Quality matters more than the bill

Claude Sonnet 5

Highest overall LiveBench score of the two at 74.6.

The workload is coding or agentic work

Claude Sonnet 5

Leads on coding — 82.2 against 48.1.

You need to fit large documents in one call

Claude Sonnet 5

Wider context window — 1M against 200K.

Claude Haiku 4.5 vs Claude Sonnet 5 FAQ

Which is better, Claude Haiku 4.5 or Claude Sonnet 5?

Claude Sonnet 5 scores higher, Claude Haiku 4.5 costs less — it depends on your workload. Claude Sonnet 5 is ahead by 28.6 points overall, and Claude Haiku 4.5 lists 2.0× cheaper per blended million tokens. Whether 28.6 points is worth that depends on how much a wrong answer costs you. Claude Haiku 4.5 also leads on measured cost per point of capability, at $0.3893 per point.

Is Claude Haiku 4.5 cheaper than Claude Sonnet 5?

Claude Haiku 4.5 is cheaper. On a 3:1 input:output blend, Claude Haiku 4.5 lists at $2.00 per million tokens and Claude Sonnet 5 at $4.00 — Claude Haiku 4.5 is 2.0× cheaper. Input and output are priced separately — Claude Haiku 4.5 charges $1.00 in and $5.00 out, Claude Sonnet 5 charges $2.00 and $10.00 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Claude Haiku 4.5 vs Claude Sonnet 5: which scores higher on benchmarks?

Claude Haiku 4.5 scores 46.0 and Claude Sonnet 5 scores 74.6 overall on LiveBench, the mean of its seven categories. That is a 28.6-point lead for Claude Sonnet 5. Category scores differ from the overall figure — a model can lead on reasoning and trail on coding, which the per-category table above breaks out.

Which gives better value for money, Claude Haiku 4.5 or Claude Sonnet 5?

Claude Haiku 4.5. Cost per point divides the measured dollars LiveBench spent running the benchmark by the score it earned, so it captures something token pricing misses: a reasoning model can emit many times more tokens than its per-token rate suggests. Claude Haiku 4.5 works out at $0.3893 per point and Claude Sonnet 5 at $2.28.

Does Claude Haiku 4.5 or Claude Sonnet 5 have a bigger context window?

Claude Sonnet 5 has the larger context window: 200K for Claude Haiku 4.5 against 1M for Claude Sonnet 5. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.

Do Claude Haiku 4.5 and Claude Sonnet 5 support prompt caching?

Both publish a cached-input rate: $0.100 per million for Claude Haiku 4.5 and $0.200 for Claude Sonnet 5, against full input rates of $1.00 and $2.00. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.

Related comparisons

How these numbers are produced

  • Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
  • Scores — LiveBench release 2026-09-02, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
  • Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
  • “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.

Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.