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Model Pareto

GPT-6.1 Terra vs GPT-5.6 Terra

GPT-6.1 Terra scores higher than GPT-5.6 Terra in both shared categories. GPT-5.6 Terra costs 2.3× as much as GPT-6.1 Terra ($4.50 vs $2.00 per million tokens, blended 3:1 input:output).
GPT-6.1 TerraGPT-5.6 Terra
Focus

Coding: quality vs price

Compared models are ringed; the other 132 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, GPT-6.1 Terra, Kimi K3.1 Pro, Claude Opus 5.5. 41 models are not plotted: Muse Wonder Full, GLM-5.3 Flash NVFP4, DeepSeek V4.1 Flash NVFP4, DeepSeek-V4-Pro-0813-nvfp4-DSpark, GLM-5.3 NVFP4, Atria Dawn Preview, Xing4.0-29B-A4B, Ternary Bonsai 27B, Beam 1.0 501B A23B, Maple-Preview, Qwen3.8 27B NVFP4, Intern-S2-397B, Bonsai 27B, Solar Open2 250B, Muse Spark Open, Laguna S 2.1, Phi-4-reasoning-plus, Flint, Motif 3, Nex-N2-Pro, Nemotron 3.5 Super VL NVFP4, Nemotron 3.5 Super VL, K2 Horizon 375B A23B, K-EXAONE 2.0 0803, A.X-K2, Nemotron 3.5 Bolt 74B-A9B, Intern-S2-Preview (35B-A3B), K2 Horizon MoVA 36B A4B, North Mini Code, G9v3-39A5B, Qwen3.8 Flash-Next NVFP4, K2 Horizon 7B, K2-Horizon-32B, LFM2.5-24B-A2B, NVIDIA Nemotron-Labs Dory1.0 4B, MiniCPM5-2B, Falcon-H1-34B-Instruct, Ling 3.0 Tiny, K2 Horizon 3.7B, K2 Horizon 0.9B, LFM2.5-2.6B.

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

Muse Wonder Full, GLM-5.3 Flash NVFP4, DeepSeek V4.1 Flash NVFP4, DeepSeek-V4-Pro-0813-nvfp4-DSpark, GLM-5.3 NVFP4, Atria Dawn Preview, Xing4.0-29B-A4B, Ternary Bonsai 27B, Beam 1.0 501B A23B, Maple-Preview, Qwen3.8 27B NVFP4, Intern-S2-397B, Bonsai 27B, Solar Open2 250B, Muse Spark Open, Laguna S 2.1, Phi-4-reasoning-plus, Flint, Motif 3, Nex-N2-Pro, Nemotron 3.5 Super VL NVFP4, Nemotron 3.5 Super VL, K2 Horizon 375B A23B, K-EXAONE 2.0 0803, A.X-K2, Nemotron 3.5 Bolt 74B-A9B, Intern-S2-Preview (35B-A3B), K2 Horizon MoVA 36B A4B, North Mini Code, G9v3-39A5B, Qwen3.8 Flash-Next NVFP4, K2 Horizon 7B, K2-Horizon-32B, LFM2.5-24B-A2B, NVIDIA Nemotron-Labs Dory1.0 4B, MiniCPM5-2B, Falcon-H1-34B-Instruct, 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 Terra
    Quality
    84.0
    Rank
    #10/134
    Price
    $2.00/M tok
    Speed
    91tok/s
    In$1.00▾Out$5.00▾/M tok

    vs GPT-5.6 Terra: +14.6 quality · 0.44× price

  • GPT-5.6 Terra
    Quality
    69.5
    Rank
    #22/134
    Price
    $4.50/M tok
    Speed
    104tok/s
    In$2.00Out$12/M tok

    vs GPT-6.1 Terra: −14.6 quality · 2.3× price

Overview

Lab
OpenAI
OpenAI
Released
Oct 26, 2026
Jul 9, 2026
Weights
Proprietary
Proprietary
Input price
$/M tok
$1.00Best
$2.00
Output price
$/M tok
$5.00Best
$12
Blended price
$/M tok · 3:1 in:out
$2.00Best
$4.50
Output speed
tok/s
91
104Best
Context
tokens
1.1MBest
1M

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.

84.0±10.2Best
#10/134Lab-reportedbest value
69.5±5.3
#22/134Mixed
Not ranked
69.0±3.3
#29/160Verified
Not ranked
76.9±4.8
#13/97Verified
90.0±8.3Best
#11/215Verifiedbest value
79.1±3.7
#26/215Verified
Not ranked
71.4±3.2
#27/186Mixed

Coding benchmarks

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

~#2/20~93.4%Estimated
estimated from related benchmarks
~#2/20~85.4%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.

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.