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Model Pareto

GPT-6.1 Sol vs Muse Spark 1.3

GPT-6.1 Sol scores higher in coding, writing & chat, vision and hard reasoning; Muse Spark 1.3 in agents. GPT-6.1 Sol costs 2× as much as Muse Spark 1.3 ($4.00 vs $2.00 per million tokens, blended 3:1 input:output).
GPT-6.1 SolMuse Spark 1.3
Focus

Coding: quality vs price

Compared models are ringed; the other 117 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
  • GPT-6.1 Sol
    Quality
    85.7
    Rank
    #5/119
    Price
    $4.00/M tok
    Speed
    53tok/s
    In$2.00Out$10/M tok

    vs Muse Spark 1.3: +13.1 quality · 2× price

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

    vs GPT-6.1 Sol: −13.1 quality · 0.5× price

Overview

Lab
OpenAI
Meta
Released
Sep 29, 2026
Sep 2, 2026
Weights
Proprietary
Proprietary
Input price
$/M tok
$2.00
$1.25Best
Output price
$/M tok
$10
$4.25Best
Blended price
$/M tok · 3:1 in:out
$4.00
$2.00Best
Output speed
tok/s
53
209Best
Context
tokens
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.

85.7±4.5Best
#5/119Verified
72.6±4.5
#11/119Verified
81.9±6.0Best
#8/156Verified
78.6±4.6
#10/156Verifiedbest value
92.5±6.2Best
#3/91Verifiedbest value
78.4±4.8
#8/91Verified
91.6±5.1Best
#7/200Verified
86.9±3.7
#8/200Verifiedbest value
82.5±7.8
#11/178Verified
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.

~#2/14~89.6%Estimated
estimated from related benchmarks
~#2/14~88.2%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
~#2/3~71.3%Estimated
estimated from related benchmarks
~#2/8~91.1%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.

Not comparable across labs (2)