Skip to main content

Perplexity: Sonar

Perplexity: Sonar is perplexity's model. On the un-leaked meo benchmark it ranks #74 of 82 with 45.6% accuracy and an Effective Value (𝕍) of 0.0001 β€” earning a correct answer for about $0.0119 in 6.93s each.

as of 2026-10-18

meo rank
#74
of 82
Accuracy
45.6%
overall
𝕍 index (top=100)
0.004
raw 𝕍 0.0001 Β· N=10
$ / correct
$0.0119
6.93s each

Per-domain accuracy

112 correct of 250 questions asked across 11 domains Β· answer rate 100% Β· macro accuracy 38.9%. Headline accuracy is micro-averaged per meo’s methodology; per-domain question counts (correct/asked) are shown so you can judge significance.

Base-rate bias
66%27/41
CSP (unsatisfiable)
50%8/16
Perceptual illusions
50%51/102
Watson-Glaser
50%2/4
Regex automaton
38%6/16
Logic / math / CS
35%12/34
Tape machine
33%5/15
Framework bias
33%1/3
State tracking
0%0/1
Theory of mind
0%0/3
Long arithmetic
0%0/15

Efficiency

Cost per correct
$0.0119
Seconds per correct
6.93
Tokens per correct
75
Correct answers
112 / 250
Total benchmark cost
$1.33
Avg tokens / item
33

Model details

Released
2025-01-27
Weights
β€”
Context
127K
Max output
114K
Knowledge cutoff
β€”
Price in
$1.00/M
Price out
$1.00/M
Modality
text+image->text

Sources: openrouter Β· meo

FAQ

How accurate is Perplexity: Sonar?

Perplexity: Sonar scores 45.6% overall on the meo benchmark (rank #74 of 82), an un-leaked private holdout graded objective-first.

What is Perplexity: Sonar's Effective Value?

Its Effective Value (𝕍) is 0.0001 at N=10, Ο‰=1, Ξ΄=1.5 β€” a fused metric of accuracy, speed, cost, and error-cascade. 𝕍 rankings shift with task depth.

How much does Perplexity: Sonar cost per correct answer?

About $0.0119 per correct answer (75 tokens, 6.93 seconds each) at benchmark-time pricing via OpenRouter.

Is Perplexity: Sonar open weights?

Open-weights status for Perplexity: Sonar is not recorded.

Benchmark updates affecting this model

  • 2026-06-09majorlogic_math_cs ground truth was broken β€” culled and rebuilt with solver-verified items

    A 5-lab frontier jury revealed that 29 of 37 LLM-authored logic_math_cs items had broken ground truth: on most, five independent frontier models unanimously concluded the clue sets were contradictory while the stored answer claimed a number, and on eight, all five agreed on the SAME different number (author arithmetic errors). Models were being marked wrong for being right. The 29 were retired (full audit published in the repo) and the domain rebuilt with generator-as-oracle items: an embedded constraint solver PROVES each puzzle has exactly one solution (or provably none), verified by an independent exhaustive enumerator. A 3-round difficulty study found frontier models saturate consistent human-scale logic puzzles, so items use anonymous global constraints and carry a measured difficulty gradient.

  • 2026-06-08majorCorrected base_bias grading (LLM-equivalence judge fix)

    The LLM-equivalence grader uses a reasoning model whose verdict token budget was too small, so its YES/NO answer was emitted as empty and silently counted as a failure. This understated the base_bias domain to ~7% for every model when the true accuracy is ~85-90%. We raised the judge budget, excluded its reasoning tokens from the verdict, switched to verbosity-robust conclusion matching, and re-graded the whole board.

Full benchmark changelog β†’

Embed this ranking

Show Perplexity: Sonar’s meo rank on your site β€” the badge links back here.

Related: all Perplexity models Β· Base-rate bias domain Β· best Effective Value Β· biggest movers Β· methodology Β· full leaderboard.