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Claude Sonnet 4.6 vs Sonar Pro Search

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 4.6 and Sonar Pro Search are priced within ~10% of each other.

Sonar Pro Search does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

anthropic

Claude Sonnet 4.6

Blended / 1M
$6.00
Context
1M
Released
Feb 17, 2026
Overall score
73.0
reasoningtool callingimage inputfile inputprompt caching

perplexity

Sonar Pro Search

Blended / 1M
$6.00
Context
200K
Released
Oct 30, 2025
Overall score
Not evaluated
reasoningimage input

Specs and pricing

MetricClaude Sonnet 4.6Sonar Pro Search
LiveBench overall

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

73.0
Cost per point

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

$0.1561
Blended price / 1M

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

$6.00$6.00
Input price / 1M$3.00$3.00
Output price / 1M$15.00$15.00
Cached input / 1M

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

$0.300
Context window1Mwin200K
Max output tokens128Kwin8K

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude Sonnet 4.6 on top, Sonar Pro Search below, both out of 100.

Agentic coding
42.6
Coding
79.3
Reasoning
84.8
Mathematics
87.0
Data analysis
77.9
Language
76.1
Instruction following
63.2

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 Sonnet 4.6Sonar Pro Search
Support chatbot

1.2K in / 400 out × 200K requests

$1,726/mo$1,920/mo
RAG assistant

8K in / 600 out × 100K requests

$2,220/mo$3,300/mo
Coding agent

40K in / 4K out × 20K requests

$2,088/mo$3,600/mo
Document extraction

20K in / 1.5K out × 50K requests

$3,990/mo$4,125/mo
Bulk classification

500 in / 20 out × 5M requests

$7,650/mo$9,000/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

Claude Sonnet 4.6

Wider context window — 1M against 200K.

Claude Sonnet 4.6 vs Sonar Pro Search FAQ

Which is better, Claude Sonnet 4.6 or Sonar Pro Search?

Claude Sonnet 4.6 and Sonar Pro Search are priced within ~10% of each other. Sonar Pro Search does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.

Is Claude Sonnet 4.6 cheaper than Sonar Pro Search?

They cost about the same. Both land near $6.00 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.

Does Claude Sonnet 4.6 or Sonar Pro Search have a bigger context window?

Claude Sonnet 4.6 has the larger context window: 1M for Claude Sonnet 4.6 against 200K for Sonar Pro Search. 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 Sonnet 4.6 and Sonar Pro Search support prompt caching?

Claude Sonnet 4.6 publishes a cached-input rate of $0.300 per million tokens against a full input rate of $3.00. The catalogue lists no separate cached rate for Sonar Pro Search, which means the provider does not price it separately here — not that caching is unavailable.

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.
  • ScoresLiveBench release 2026-06-25, 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.