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Model Pareto

Compare models

Side by side: quality per category, price, speed, and every benchmark cell with where it came from. Pick up to four.
Celeris-1Gemini Omni 1.1 FlashGemini Omni FlashWan 3.0Up to 4 models — remove one to add another.

Overview

Lab
Celeris
Google DeepMind
Google DeepMind
Alibaba Qwen
Released
Jul 24, 2026
Aug 27, 2026
May 19, 2026
Aug 19, 2026
Weights
Proprietary
Proprietary
Proprietary
Proprietary
Input price
$/M tok
$0.20
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Output price
$/M tok
$0.70
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Blended price
$/M tok · 3:1 in:out
$0.325
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Output speed
tok/s
1521
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Context
tokens
131K
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Price per second
1080p
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$0.10Best
$0.10Best
$0.20

Quality by category

0–100 within each category (100 = best tracked model). Rank is among all models ranked there. Click a row to focus it.

15.6±8.0
#98/103Verified
Not ranked
Not ranked
Not ranked
24.5±3.7
#125/182Verified
Not ranked
Not ranked
Not ranked
16.1±5.8
#154/173Verified
Not ranked
Not ranked
Not ranked
Not ranked
94.3±6.3
#2/34Verified
96.9±3.0Best
#1/34Verifiedbest value
93.8±4.1
#3/34Verified

Coding benchmarks

Rank among models with a published score, and the leaderboard around each model. ~ italic = no published score, estimated from related benchmarks.

Hard reasoning benchmarks

Rank among models with a published score, and the leaderboard around each model. ~ italic = no published score, estimated from related benchmarks.

Agents benchmarks

Rank among models with a published score, and the leaderboard around each model. ~ italic = no published score, estimated from related benchmarks.

Video generation benchmarks

Rank among models with a published score, and the leaderboard around each model. ~ italic = no published score, estimated from related benchmarks.

VBench
day 0
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