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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.
GPT-6 SolKimi K3MiMo-V2.6-Pro
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
  • GPT-6 Sol
    Quality
    78.7
    Rank
    #6/103
    Price
    $4.00/M tok
    Speed
    110tok/s
    In$2.00Out$10/M tok

    vs MiMo-V2.6-Pro: +0.9 quality · 7.4× price

  • Kimi K3
    Quality
    65.2
    Rank
    #16/103
    Price
    $6.00/M tok
    Speed
    37tok/s
    In$3.00Out$15/M tok

    vs GPT-6 Sol: −13.5 quality · 1.5× price

  • MiMo-V2.6-Pro
    Quality
    77.8
    Rank
    #7/103
    Price
    $0.54/M tok
    Speed
    49tok/s
    In$0.435▾Out$0.87▾/M tok

    vs GPT-6 Sol: −0.9 quality · 0.14× price

Overview

Lab
OpenAI
Moonshot AI (Kimi)
Xiaomi MiMo
Released
Sep 22, 2026
Jul 16, 2026
Sep 21, 2026
Weights
Proprietary
Open
Open
Input price
$/M tok
$2.00
$3.00
$0.435Best
Output price
$/M tok
$10
$15
$0.87Best
Blended price
$/M tok · 3:1 in:out
$4.00
$6.00
$0.544Best
Output speed
tok/s
110Best
37
49
Context
tokens
872K
1MBest
1M

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.

78.7±4.5Best
#6/103Verified
65.2±4.5
#16/103Verified
77.9±6.4
#7/103Mixedbest value
83.1±4.3
#7/146Verified
89.1±4.3Best
#5/146Verifiedbest value
81.8±6.0
#11/146Verifiedbest value
86.8±4.8Best
#4/82Verifiedbest value
77.0±3.9
#11/82Mixed
76.5±9.4
#12/82Verified
85.8±5.1
#8/182Verified
83.4±3.7
#9/182Verified
86.1±5.1Best
#7/182Verifiedbest value
76.0±7.8
#17/173Verified
82.4±3.5
#12/173Mixed
84.4±6.4Best
#9/173Mixed

Coding benchmarks

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

~#2/14~89.3%Estimated
estimated from related benchmarks
~#2/14~85.3%Estimated
estimated from related benchmarks
~#2/14~89.6%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
~#2/5~90.4%Estimated
estimated from related benchmarks
~#2/5~92.0%Estimated
estimated from related benchmarks
~#2/5~90.9%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

Hard reasoning benchmarks

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

~#2/25~96.5%Estimated
estimated from related benchmarks
~#2/25~96.8%Estimated
estimated from related benchmarks
~#2/25~96.5%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.

~#2/116~98.2%Estimated
estimated from related benchmarks
~#2/116~98.3%Estimated
estimated from related benchmarks
~#2/116~98.1%Estimated
estimated from related benchmarks
Not comparable across labs (1)