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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 Opus 5.5Granite 4.2 3BTernary Bonsai 2 27B
Focus

Coding: quality vs price

Compared models are ringed; the other 111 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, Qwen3.8-Omni-Flash, GLM-5.3 Flash, DeepSeek V4.1 Flash, MiMo-V2.6-Pro, Claude Sonnet 5.5, Claude Opus 5.5. 36 models are not plotted: GLM-5.3 Flash NVFP4, Ternary Bonsai 2 27B, DeepSeek V4.1 Flash NVFP4, GLM-5.3 NVFP4, Nex-N2.5-Pro, Xing4.0-29B-A4B, Atria Dawn Preview, Ternary Bonsai 27B, Maple-Preview, Bonsai 27B, Qwen3.8 27B NVFP4, 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, Qwen3.8 Flash-Next NVFP4, Devstral 2, K2 Horizon 7B, K2-Horizon-32B, Devstral Small 2, MiniCPM5-2B, Ling 3.0 Tiny, K2 Horizon 3.7B, K2 Horizon 0.9B, LFM2.5-2.6B.

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

GLM-5.3 Flash NVFP4, Ternary Bonsai 2 27B, DeepSeek V4.1 Flash NVFP4, GLM-5.3 NVFP4, Nex-N2.5-Pro, Xing4.0-29B-A4B, Atria Dawn Preview, Ternary Bonsai 27B, Maple-Preview, Bonsai 27B, Qwen3.8 27B NVFP4, 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, Qwen3.8 Flash-Next NVFP4, Devstral 2, K2 Horizon 7B, K2-Horizon-32B, 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 Opus 5.5
    Quality
    96.6
    Rank
    #1/114
    Price
    $8.00/M tok
    Speed
    92tok/s
    In$4.00Out$20/M tok

    vs Ternary Bonsai 2 27B: +24.9 quality · price n/a

  • Granite 4.2 3B
    Quality
    17.8
    Rank
    #107/114
    Price
    $0.05/M tok
    Speed
    220tok/s
    In$0.03▾Out$0.12▾/M tok

    vs Claude Opus 5.5: −78.9 quality · 0.01× price

  • Ternary Bonsai 2 27B
    Quality
    71.8
    Rank
    #13/114
    Price
    —
    Speed
    —

    vs Claude Opus 5.5: −24.9 quality · price n/a

Overview

Lab
Anthropic
IBM Granite
PrismML
Released
Sep 22, 2026
Aug 25, 2026
Sep 16, 2026
Weights
Proprietary
Open
Open
Input price
$/M tok
$4.00
$0.03Best
—
Output price
$/M tok
$20
$0.12Best
—
Blended price
$/M tok · 3:1 in:out
$8.00
$0.052Best
—
Output speed
tok/s
92
220Best
—
Context
tokens
1MBest
131K
262K

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.

96.6±3.5Best
#1/114Mixedbest value
17.8±8.0
#107/114Verifiedbest value
71.8±10.3
#13/114Lab-reported
93.0±4.3Best
#3/155Verifiedbest value
Not ranked
76.9±9.7
#21/155Lab-reported
94.6±4.8Best
#2/90Verifiedbest value
Not ranked
69.0±8.7
#20/90Lab-reported
99.9±2.6Best
#1/193Verifiedbest value
23.2±3.7
#138/193Verified
74.4±9.9
#28/193Lab-reported
99.6±4.1Best
#1/176Verifiedbest value
17.1±5.8
#143/176Verified
Not ranked

Coding benchmarks

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

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
—
~#2/8~91.4%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.

Agents benchmarks

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

~#2/12~84.6%Estimated
estimated from related benchmarks
—
~#2/5~58.7%Estimated
estimated from related benchmarks
~last/5below measured range (<47.5%)Estimated
estimated from related benchmarks
—
Not comparable across labs (1)