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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.
Kimi K2.7 CodeQwen3.7 PlusSolar Pro 4
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
  • Kimi K2.7 Code
    Quality
    40.2
    Rank
    #43/103
    Price
    $1.71/M tok
    Speed
    66tok/s
    In$0.95Out$4.00/M tok

    vs Qwen3.7 Plus: +0.7 quality · 2.4× price

  • Qwen3.7 Plus
    Quality
    39.5
    Rank
    #45/103
    Price
    $0.70/M tok
    Speed
    65tok/s
    In$0.40Out$1.60/M tok

    vs Kimi K2.7 Code: −0.7 quality · 0.41× price

  • Solar Pro 4
    Quality
    37.5
    Rank
    #49/103
    Price
    $0.52/M tok
    Speed
    93tok/s
    In$0.30▾Out$1.20▾/M tok

    vs Kimi K2.7 Code: −2.7 quality · 0.31× price

Overview

Lab
Moonshot AI (Kimi)
Alibaba Qwen
Upstage
Released
Jun 12, 2026
Jun 1, 2026
Aug 6, 2026
Weights
Open
Proprietary
Proprietary
Input price
$/M tok
$0.95
$0.40
$0.30Best
Output price
$/M tok
$4.00
$1.60
$1.20Best
Blended price
$/M tok · 3:1 in:out
$1.712
$0.70
$0.525Best
Output speed
tok/s
66
65
93Best
Context
tokens
256K
1MBest
512K

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.

40.2±8.0Best
#43/103Verified
39.6±8.0
#45/103Verified
37.5±8.0
#49/103Verified
56.4±9.5
#51/146Verified
72.9±4.2Best
#21/146Verified
Not ranked
Not ranked
62.9±6.3
#27/82Verified
Not ranked
65.4±3.7
#37/182Verified
65.6±3.7Best
#36/182Verified
64.7±5.8
#38/182Verified
45.3±4.2
#47/173Verified
42.3±4.2
#53/173Verified
47.9±10.0Best
#36/173Verified

Coding benchmarks

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

~#14/19~56.0%Estimated
estimated from related benchmarks
~#14/19~55.7%Estimated
estimated from related benchmarks
~#14/19~54.6%Estimated
estimated from related benchmarks
~last/15below measured range (<41.1)Estimated
estimated from related benchmarks
~last/15below measured range (<41.1)Estimated
estimated from related benchmarks
~last/15below measured range (<41.1)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
~#2/5~88.9%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.

Hard reasoning benchmarks

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

~#4/25~94.3%Estimated
estimated from related benchmarks
~#2/25~95.0%Estimated
estimated from related benchmarks
~#2/25~94.7%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.

~last/5below measured range (<47.5%)Estimated
estimated from related benchmarks
~last/5below measured range (<47.5%)Estimated
estimated from related benchmarks
~last/5below measured range (<47.5%)Estimated
estimated from related benchmarks