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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.
GLM-5.3GPT-5.5GPT-5.6 Terra
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
  • GLM-5.3
    Quality
    74.0
    Rank
    #9/103
    Price
    $2.15/M tok
    Speed
    57tok/s
    In$1.40▾Out$4.40▾/M tok

    vs GPT-5.6 Terra: +4.2 quality · 0.48× price

  • GPT-5.5
    Quality
    60.2
    Rank
    #22/103
    Price
    $11.3/M tok
    Speed
    91tok/s
    In$5.00Out$30/M tok

    vs GLM-5.3: −13.8 quality · 5.2× price

  • GPT-5.6 Terra
    Quality
    69.8
    Rank
    #12/103
    Price
    $4.50/M tok
    Speed
    83tok/s
    In$2.00Out$12/M tok

    vs GLM-5.3: −4.2 quality · 2.1× price

Overview

Lab
Z.ai (Zhipu)
OpenAI
OpenAI
Released
Aug 14, 2026
Apr 23, 2026
Jul 9, 2026
Weights
Open
Proprietary
Proprietary
Input price
$/M tok
$1.40Best
$5.00
$2.00
Output price
$/M tok
$4.40Best
$30
$12
Blended price
$/M tok · 3:1 in:out
$2.15Best
$11.3
$4.50
Output speed
tok/s
57
91Best
83
Context
tokens
1MBest
922K
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.

74.0±4.5Best
#9/103Verified
60.2±5.2
#22/103Mixed
69.8±5.2
#12/103Mixed
86.0±4.3Best
#6/146Verifiedbest value
77.0±3.3
#16/146Verified
71.7±3.3
#23/146Verified
Not ranked
74.4±4.8
#14/82Verified
78.1±4.8Best
#8/82Verified
81.0±3.7Best
#15/182Verified
79.9±3.7
#17/182Verified
80.1±3.7
#16/182Verified
87.4±5.8Best
#4/173Verified
67.4±3.2
#26/173Mixed
72.3±3.2
#22/173Mixed

Coding benchmarks

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

~#2/14~89.7%Estimated
estimated from related benchmarks
~#2/14~85.8%Estimated
estimated from related benchmarks
LiveCodeBench
third-party
~#2/20~92.1%Estimated
estimated from related benchmarks
~#2/20~92.1%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.

MMMLU
day 0
~#2/5~91.3%Estimated
estimated from related benchmarks
~#2/5~91.3%Estimated
estimated from related benchmarks
~#2/5~90.4%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
—
~#4/8~89.8%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.

~#2/25~96.7%Estimated
estimated from related benchmarks
~#2/25~96.8%Estimated
estimated from related benchmarks
~#2/25~96.8%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.