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Sonar vs Sonar Deep Research

Updated October 21, 2026. 0 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

SonarPerplexity
Coding
No data
Overall
7.7
Output $/M
$1.00
Sonar Deep ResearchPerplexity
Coding
No data
Overall
No data
Output $/M
$8.00
vs $1.00 vs $8.00 per 1M output tokens. Sonar is 8.0x cheaper.

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Sonar has the edge where output tokens cost 8.0x less.

Shared results
0
Sonar only
5
Sonar Deep Research only
0
Like-for-like categories
0 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Sonar not benchmarked, Sonar Deep Research not benchmarked.
Widest category
No category has a result for both models.
Widest single gap
No benchmark has a result for both models.
Output price
Sonar $1.00 against Sonar Deep Research $8.00 per million output tokens, 8.0x apart.
Context window
Sonar takes 127K tokens, Sonar Deep Research 128K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

CodingDirectional onlySix of these boards feed the Vibe Coding Index1 board, none shared
Coding benchmarks for Sonar and Sonar Deep Research
BenchmarkSonarSonar Deep ResearchLeader
LiveCodeBench (Artificial Analysis run)29.5%Not measuredOnly Sonar measured
Neither model has a result on the other 37 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Sonar and Sonar Deep Research
BenchmarkSonarSonar Deep ResearchLeader
AA Intelligence Index7.7Not measuredOnly Sonar measured
Neither model has a result on the other 1 board here
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Agentic work benchmarks for Sonar and Sonar Deep Research
BenchmarkSonarSonar Deep ResearchLeader
Neither model has a result on 39 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Reasoning benchmarks for Sonar and Sonar Deep Research
BenchmarkSonarSonar Deep ResearchLeader
GPQA Diamond (Artificial Analysis run)47.1%Not measuredOnly Sonar measured
Humanity's Last Exam (Artificial Analysis run)4.9%Not measuredOnly Sonar measured
Neither model has a result on the other 19 boards here
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Math benchmarks for Sonar and Sonar Deep Research
BenchmarkSonarSonar Deep ResearchLeader
Neither model has a result on 13 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Knowledge benchmarks for Sonar and Sonar Deep Research
BenchmarkSonarSonar Deep ResearchLeader
MMLU Pro (Artificial Analysis run)68.9%Not measuredOnly Sonar measured
Neither model has a result on the other 16 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Sonar and Sonar Deep Research
BenchmarkSonarSonar Deep ResearchLeader
Neither model has a result on 9 boards here
GeneralNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
General benchmarks for Sonar and Sonar Deep Research
BenchmarkSonarSonar Deep ResearchLeader
Neither model has a result on 46 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Sonar and Sonar Deep Research
BenchmarkSonarSonar Deep ResearchLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Sonar$0.0015Fits in one request
Sonar Deep Research$0.0060Fits in one request

Sonar costs less

Repository review

50K input + 3K output tokens

Sonar$0.053Fits in one request
Sonar Deep Research$0.124Fits in one request

Sonar costs less

Agent loop

200K input + 10K output tokens

Sonar$0.210Exceeds the context window
Sonar Deep Research$0.480Exceeds the context window

Sonar costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Sonar and Sonar Deep Research
SpecificationPerplexity SonarPerplexity Sonar Deep Research
MakerPerplexityPerplexity
WeightsNo public weights listedNo public weights listed
ReleasedJanuary 27, 2025March 7, 2025
Context window127K128K
Input $/Mtok$1.00$2.00
Output $/Mtok$1.00$8.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Sonar better than Sonar Deep Research for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Sonar has the edge where output tokens cost 8.0x less.

Which is cheaper, Sonar or Sonar Deep Research?

Sonar costs $1.00 per million input tokens and $1.00 per million output tokens; Sonar Deep Research costs $2.00 and $8.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Sonar or Sonar Deep Research?

Sonar Deep Research, with 128K tokens against 127K.

How many benchmarks is the Sonar vs Sonar Deep Research comparison based on?

0 benchmarks have a result for both models as of October 21, 2026. Sonar's coding index rests on 0 independent benchmarks and Sonar Deep Research's on 0. Where only one model has a result, the page says so instead of naming a winner.

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