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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.
Claude Fable 5.1GPT-6 AstraClaude Opus 5.5
Focus

Coding: quality vs price

Compared models are ringed; the other 100 ranked here are greyed.

Lower price is better. Pareto frontier: Granite 4.2 3B, NVIDIA Nemotron 3 Nano 30B A3B, gpt-oss-20b, Ling-3.0-flash-VL, MiMo-V2.6-Flash, GLM-5.3 Flash, DeepSeek V4.1 Flash, MiMo-V2.6-Pro, Claude Sonnet 5.5, Claude Opus 5.5. 26 models are not plotted: Xing4.0-29B-A4B, Nex-N2.5-Pro, Atria Dawn Preview, Intern-S2-397B, Solar Open2 250B, Phi-4-reasoning-plus, Motif 3, Nex-N2-Pro, Nex-N2.5-Mini, A.X-K2, K2 Horizon 375B A23B, K-EXAONE 2.0 0803, K2 Horizon MoVA 36B A4B, Intern-S2-Preview (35B-A3B), Command A+, North Mini Code, G9v3-39A5B, Falcon-H1-34B-Instruct, Devstral 2, K2 Horizon 7B, Devstral Small 2, MiniCPM5-2B, Ling 3.0 Tiny, K2 Horizon 3.7B, K2 Horizon 0.9B, LFM2.5-2.6B.

26 models with no price data — shown in the strip at the left edge

Xing4.0-29B-A4B, Nex-N2.5-Pro, Atria Dawn Preview, Intern-S2-397B, Solar Open2 250B, Phi-4-reasoning-plus, Motif 3, Nex-N2-Pro, Nex-N2.5-Mini, A.X-K2, K2 Horizon 375B A23B, K-EXAONE 2.0 0803, K2 Horizon MoVA 36B A4B, Intern-S2-Preview (35B-A3B), Command A+, North Mini Code, G9v3-39A5B, Falcon-H1-34B-Instruct, Devstral 2, K2 Horizon 7B, Devstral Small 2, MiniCPM5-2B, Ling 3.0 Tiny, K2 Horizon 3.7B, K2 Horizon 0.9B, LFM2.5-2.6B

  • Best-value frontier (nothing is both cheaper and better)
  • Evidencestrong → weak
  • Estimated from other categories
  • Claude Fable 5.1
    Quality
    87.5
    Rank
    #3/103
    Price
    $20.0/M tok
    Speed
    66tok/s
    In$10Out$50/M tok

    vs Claude Opus 5.5: −9.3 quality · 2.5× price

  • GPT-6 Astra
    Quality
    86.2
    Rank
    #4/103
    Price
    $20.0/M tok
    Speed
    52tok/s
    In$10Out$50/M tok

    vs Claude Opus 5.5: −10.7 quality · 2.5× price

  • Claude Opus 5.5
    Quality
    96.9
    Rank
    #1/103
    Price
    $8.00/M tok
    Speed
    92tok/s
    In$4.00▾Out$20▾/M tok

    vs Claude Fable 5.1: +9.3 quality · 0.4× price

Overview

Lab
Anthropic
OpenAI
Anthropic
Released
Sep 1, 2026
Sep 3, 2026
Sep 22, 2026
Weights
Proprietary
Proprietary
Proprietary
Input price
$/M tok
$10
$10
$4.00Best
Output price
$/M tok
$50
$50
$20Best
Blended price
$/M tok · 3:1 in:out
$20
$20
$8.00Best
Output speed
tok/s
66
52
92Best
Context
tokens
1MBest
1MBest
1MBest

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.

87.6±3.7
#3/103Mixed
86.2±4.5
#4/103Verified
96.9±3.4Best
#1/103Mixedbest value
97.6±3.5Best
#1/146Verifiedbest value
92.1±5.3
#4/146Verified
93.0±4.3
#3/146Verifiedbest value
87.4±7.3
#3/82Verified
98.9±3.0Best
#1/82Verifiedbest value
94.5±4.8
#2/82Verifiedbest value
95.7±3.7
#2/182Verified
93.5±3.7
#4/182Verified
99.9±2.6Best
#1/182Verifiedbest value
89.6±5.8
#2/173Verified
81.6±4.6
#15/173Mixed
99.6±4.1Best
#1/173Verifiedbest value

Coding benchmarks

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

~#2/14~93.5%Estimated
estimated from related benchmarks
~#2/14~90.0%Estimated
estimated from related benchmarks
~#2/14~94.7%Estimated
estimated from related benchmarks
LiveCodeBench
third-party
~#2/20~92.3%Estimated
estimated from related benchmarks
Benchmarks in other categories (4)

Writing & chat benchmarks

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

IFBench
day 0
~#2/126~82.8%Estimated
estimated from related benchmarks
~#2/126~82.8%Estimated
estimated from related benchmarks
MMMLU
day 0
~#2/5~92.4%Estimated
estimated from related benchmarks
~#2/5~91.4%Estimated
estimated from related benchmarks
~#2/5~92.3%Estimated
estimated from related benchmarks

Vision benchmarks

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

MMMU
day 0
~#2/3~71.3%Estimated
estimated from related benchmarks
~#2/3~71.3%Estimated
estimated from related benchmarks
~#2/3~71.3%Estimated
estimated from related benchmarks
~#2/9~86.0%Estimated
estimated from related benchmarks
~#2/9~86.1%Estimated
estimated from related benchmarks
~#2/9~86.1%Estimated
estimated from related benchmarks
~#2/8~91.2%Estimated
estimated from related benchmarks
~#2/8~91.4%Estimated
estimated from related benchmarks
~#2/8~91.4%Estimated
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.

~#2/25~96.9%Estimated
estimated from related benchmarks
~#2/25~96.9%Estimated
estimated from related benchmarks
~#2/25~96.7%Estimated
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.

~#2/116~98.3%Estimated
estimated from related benchmarks
~#2/116~98.3%Estimated
estimated from related benchmarks
~#2/116~98.3%Estimated
estimated from related benchmarks
~#2/12~84.6%Estimated
estimated from related benchmarks
~#3/12~83.4%Estimated
estimated from related benchmarks
~#2/12~84.6%Estimated
estimated from related benchmarks
~#2/5~58.7%Estimated
estimated from related benchmarks
Not comparable across labs (2)