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Model Pareto

GPT-6 Astra vs GPT-6.1 Sol

GPT-6 Astra scores higher in coding, vision and hard reasoning; GPT-6.1 Sol in writing & chat and agents. GPT-6 Astra costs 5× as much as GPT-6.1 Sol ($20.0 vs $4.00 per million tokens, blended 3:1 input:output).
GPT-6 AstraGPT-6.1 Sol
Focus

Coding: quality vs price

Compared models are ringed; the other 103 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. 27 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, K2-Horizon-32B, Devstral Small 2, MiniCPM5-2B, Ling 3.0 Tiny, K2 Horizon 3.7B, K2 Horizon 0.9B, LFM2.5-2.6B.

27 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, 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 Astra
    Quality
    86.0
    Rank
    #4/105
    Price
    $20.0/M tok
    Speed
    52tok/s
    In$10Out$50/M tok

    vs GPT-6.1 Sol: +0.7 quality · 5× price

  • GPT-6.1 Sol
    Quality
    85.3
    Rank
    #5/105
    Price
    $4.00/M tok
    Speed
    —
    In$2.00▾Out$10▾/M tok

    vs GPT-6 Astra: −0.7 quality · 0.2× price

Overview

Lab
OpenAI
OpenAI
Released
Sep 3, 2026
Sep 29, 2026
Weights
Proprietary
Proprietary
Input price
$/M tok
$10
$2.00Best
Output price
$/M tok
$50
$10Best
Blended price
$/M tok · 3:1 in:out
$20
$4.00Best
Output speed
tok/s
52
—
Context
tokens
1MBest
922K

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.

86.0±4.5Best
#4/105Verified
85.3±6.4
#5/105Mixed
92.1±5.3
#5/147Verified
92.6±10.0Best
#4/147Estimated from other categoriesbest value
98.9±3.0Best
#1/83Verifiedbest value
85.1±8.2
#5/83Verified
93.5±3.7Best
#4/184Verified
91.5±5.1
#6/184Verified
81.6±4.6
#16/175Mixed
84.7±12.5Best
#9/175Estimated from other categories

Coding benchmarks

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

~#2/14~89.9%Estimated
estimated from related benchmarks
~#2/14~90.2%Estimated
estimated from related benchmarks
LiveCodeBench
third-party
~#2/20~92.3%Estimated
estimated from related benchmarks
~#2/20~92.1%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
~#2/3~71.3%Estimated
estimated from related benchmarks
~#2/9~86.1%Estimated
estimated from related benchmarks
~#2/9~85.7%Estimated
estimated from related benchmarks
~#2/8~91.4%Estimated
estimated from related benchmarks
~#4/8~90.6%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.

~#2/116~98.3%Estimated
estimated from related benchmarks
~#2/116~97.8%Estimated
estimated from related benchmarks
Not comparable across labs (1)