Skip to content
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 Haiku 5.5Gemini 3.8 FlashMuse Spark 1.3
Focus

Coding: quality vs price

Compared models are ringed; the other 116 ranked here are greyed.

Lower price is better. Pareto frontier: Nex-N2.5-Mini, Nex-N2.5-Pro, MiMo-V2.6-Flash, Ternary Bonsai 2 27B, MiMo-V2.6-Pro, Gemini 4 Argon, Claude Opus 5.5. 34 models are not plotted: GLM-5.3 Flash NVFP4, DeepSeek V4.1 Flash NVFP4, GLM-5.3 NVFP4, DeepSeek-V4-Pro-0813-nvfp4-DSpark, Xing4.0-29B-A4B, Ternary Bonsai 27B, Atria Dawn Preview, Maple-Preview, Bonsai 27B, Qwen3.8 27B NVFP4, Intern-S2-397B, Phi-4-reasoning-plus, Solar Open2 250B, Laguna S 2.1, Motif 3, Nex-N2-Pro, K-EXAONE 2.0 0803, K2 Horizon 375B A23B, A.X-K2, K2 Horizon MoVA 36B A4B, Intern-S2-Preview (35B-A3B), 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.

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

GLM-5.3 Flash NVFP4, DeepSeek V4.1 Flash NVFP4, GLM-5.3 NVFP4, DeepSeek-V4-Pro-0813-nvfp4-DSpark, Xing4.0-29B-A4B, Ternary Bonsai 27B, Atria Dawn Preview, Maple-Preview, Bonsai 27B, Qwen3.8 27B NVFP4, Intern-S2-397B, Phi-4-reasoning-plus, Solar Open2 250B, Laguna S 2.1, Motif 3, Nex-N2-Pro, K-EXAONE 2.0 0803, K2 Horizon 375B A23B, A.X-K2, K2 Horizon MoVA 36B A4B, Intern-S2-Preview (35B-A3B), 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 Haiku 5.5
    Quality
    66.2
    Rank
    #19/119
    Price
    $0.20/M tok
    Speed
    —
    In$0.10▾Out$0.50▾/M tok

    vs Muse Spark 1.3: −6.4 quality · 0.1× price

  • Gemini 3.8 Flash
    Quality
    55.4
    Rank
    #37/119
    Price
    $1.50/M tok
    Speed
    129tok/s
    In$0.75Out$3.75/M tok

    vs Muse Spark 1.3: −17.2 quality · 0.75× price

  • Muse Spark 1.3
    Quality
    72.6
    Rank
    #11/119
    Price
    $2.00/M tok
    Speed
    209tok/s
    In$1.25Out$4.25/M tok

    vs Claude Haiku 5.5: +6.4 quality · 10× price

Overview

Lab
Anthropic
Google DeepMind
Meta
Released
Oct 7, 2026
Sep 2, 2026
Sep 2, 2026
Weights
Proprietary
Proprietary
Proprietary
Input price
$/M tok
$0.10Best
$0.75
$1.25
Output price
$/M tok
$0.50Best
$3.75
$4.25
Blended price
$/M tok · 3:1 in:out
$0.20Best
$1.50
$2.00
Output speed
tok/s
—
129
209Best
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.

66.2±8.0
#19/119Verified
55.4±4.5
#37/119Verified
72.6±4.5Best
#11/119Verified
Not ranked
73.5±4.6
#22/156Verified
78.6±4.6Best
#10/156Verifiedbest value
78.7±9.7
#7/91Lab-reportedbest value
82.1±4.1Best
#6/91Mixedbest value
78.4±4.8
#8/91Verified
81.3±5.1
#17/200Verifiedbest value
82.6±3.7
#13/200Verified
86.9±3.7Best
#8/200Verifiedbest value
Not ranked
75.8±5.8
#18/178Verified
87.0±5.8Best
#4/178Verifiedbest value

Coding benchmarks

Rank among models with a published score, and the leaderboard around each model. ~ italic = no published score, 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
—
~#2/5~92.0%Estimated
estimated from related benchmarks
~#2/5~92.1%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.

~#2/32~97.9%Estimated
estimated from related benchmarks
~#2/32~99.0%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.

Not comparable across labs (1)