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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.
Qwen3.8-Omni-FlashMuse Spark 1.3GPT-5.6 Terra
Focus

Hard reasoning: quality vs price

Compared models are ringed; the other 179 ranked here are greyed.

Lower price is better. Pareto frontier: Gemma 4 E4B, Sarvam 30B, Qwen3.5 4B, Sarvam 105B, Ling 3.0 Flash, MiMo-V2.5, GPT-6 Luna, Qwen3.8 Flash-Next, GLM-5.3 Flash, MiMo-V2.6-Pro, Muse Spark 1.3, Claude Sonnet 5.5, Claude Opus 5.5. 70 models are not plotted: Motif 3, Nex-N2-Pro, K2 Horizon 375B A23B, A.X-K2, Solar Open2 250B, Xing4.0-29B-A4B, K2 Horizon MoVA 36B A4B, Intern-S2-Preview (35B-A3B), K-EXAONE 2.0 0803, G9v3-39A5B, K2 Horizon 7B, Phi-4-reasoning-plus, EXAONE 4.5 33B, Nanbeige4.1-3B, HyperNova 60B 2605, Nemotron Cascade 2 30B A3B, INTELLECT-3, Apriel-v1.6-15B-Thinker, Command A+, K2 Horizon 3.7B, Ling 3.0 Tiny, K2 Think V2, Step3 VL 10B, DiffusionGemma 26B A4B, K2-V2, North Mini Code, Falcon-H1R-7B, Solar Open 100B, Llama 3.1 Nemotron Ultra 253B v1, MiniCPM5-2B, LongCat Flash Lite, HyperCLOVA X SEED Think (32B), Tri-21B-Think, EXAONE 4.0 32B, Olmo 3.1 32B Think, LFM2.5-2.6B, Devstral 2, LFM2.5-8B-A1B, Olmo 3.1 32B Instruct, Olmo 3 7B Think, NVIDIA Nemotron 3 Nano 4B, Devstral Small 2, Phi-4-mini-flash-reasoning, Falcon-H1-34B-Instruct, Qwen3.5 2B, Hermes 4 - Llama-3.1 70B, LFM2 24B A2B, Exaone 4.0 1.2B, Llama 3.2 Instruct 90B (Vision), Gemma 4 E2B, Molmo2-8B, LFM2.5-1.2B-Thinking, LFM2.5-1.2B-Instruct, MiniCPM5-1B, Jamba 1.7 Large, MiniCPM-V 4.6 1.3B, Kimi Linear 48B A3B Instruct, Granite 4.0 Micro, Jamba Reasoning 3B, Jamba 1.7 Mini, Phi-4 Multimodal Instruct, Tiny Aya Global, LFM2.5-VL-1.6B, Granite 4.0 H 350M, K2 Horizon 0.9B, Qwen3.5 0.8B, Granite 4.0 350M, Granite 4.0 H 1B, Molmo 7B-D, Gemma 3 270M.

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

Motif 3, Nex-N2-Pro, K2 Horizon 375B A23B, A.X-K2, Solar Open2 250B, Xing4.0-29B-A4B, K2 Horizon MoVA 36B A4B, Intern-S2-Preview (35B-A3B), K-EXAONE 2.0 0803, G9v3-39A5B, K2 Horizon 7B, Phi-4-reasoning-plus, EXAONE 4.5 33B, Nanbeige4.1-3B, HyperNova 60B 2605, Nemotron Cascade 2 30B A3B, INTELLECT-3, Apriel-v1.6-15B-Thinker, Command A+, K2 Horizon 3.7B, Ling 3.0 Tiny, K2 Think V2, Step3 VL 10B, DiffusionGemma 26B A4B, K2-V2, North Mini Code, Falcon-H1R-7B, Solar Open 100B, Llama 3.1 Nemotron Ultra 253B v1, MiniCPM5-2B, LongCat Flash Lite, HyperCLOVA X SEED Think (32B), Tri-21B-Think, EXAONE 4.0 32B, Olmo 3.1 32B Think, LFM2.5-2.6B, Devstral 2, LFM2.5-8B-A1B, Olmo 3.1 32B Instruct, Olmo 3 7B Think, NVIDIA Nemotron 3 Nano 4B, Devstral Small 2, Phi-4-mini-flash-reasoning, Falcon-H1-34B-Instruct, Qwen3.5 2B, Hermes 4 - Llama-3.1 70B, LFM2 24B A2B, Exaone 4.0 1.2B, Llama 3.2 Instruct 90B (Vision), Gemma 4 E2B, Molmo2-8B, LFM2.5-1.2B-Thinking, LFM2.5-1.2B-Instruct, MiniCPM5-1B, Jamba 1.7 Large, MiniCPM-V 4.6 1.3B, Kimi Linear 48B A3B Instruct, Granite 4.0 Micro, Jamba Reasoning 3B, Jamba 1.7 Mini, Phi-4 Multimodal Instruct, Tiny Aya Global, LFM2.5-VL-1.6B, Granite 4.0 H 350M, K2 Horizon 0.9B, Qwen3.5 0.8B, Granite 4.0 350M, Granite 4.0 H 1B, Molmo 7B-D, Gemma 3 270M

  • Best-value frontier (nothing is both cheaper and better)
  • Evidencestrong → weak
  • Estimated from other categories
  • Qwen3.8-Omni-Flash
    Quality
    73.5
    Rank
    #27/182
    Price
    $0.23/M tok
    Speed
    —
    In$0.15▾Out$0.47▾/M tok

    vs Muse Spark 1.3: −13.4 quality · 0.11× price

  • Muse Spark 1.3
    Quality
    86.9
    Rank
    #6/182
    Price
    $2.00/M tok
    Speed
    219tok/s
    In$1.25Out$4.25/M tok

    vs GPT-5.6 Terra: +6.8 quality · 0.44× price

  • GPT-5.6 Terra
    Quality
    80.1
    Rank
    #16/182
    Price
    $4.50/M tok
    Speed
    83tok/s
    In$2.00Out$12/M tok

    vs Muse Spark 1.3: −6.8 quality · 2.3× price

Overview

Lab
Alibaba Qwen
Meta
OpenAI
Released
Sep 18, 2026
Sep 2, 2026
Jul 9, 2026
Weights
Proprietary
Proprietary
Proprietary
Input price
$/M tok
$0.15Best
$1.25
$2.00
Output price
$/M tok
$0.47Best
$4.25
$12
Blended price
$/M tok · 3:1 in:out
$0.23Best
$2.00
$4.50
Output speed
tok/s
—
219Best
83
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.

63.1±8.6
#18/103Lab-reported
74.9±4.5Best
#8/103Verified
69.8±5.2
#12/103Mixed
78.8±9.7
#13/146Lab-reported
82.3±4.7Best
#10/146Verified
71.7±3.3
#23/146Verified
78.6±10.2
#7/82Lab-reportedbest value
79.1±4.8Best
#6/82Verified
78.1±4.8
#8/82Verified
73.5±6.6
#27/182Lab-reported
86.9±3.7Best
#6/182Verifiedbest value
80.1±3.7
#16/182Verified
Not ranked
87.4±5.8Best
#3/173Verifiedbest value
72.3±3.2
#22/173Mixed

Hard reasoning benchmarks

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

~#2/25~96.5%Estimated
estimated from related benchmarks
~#2/25~96.8%Estimated
estimated from related benchmarks
~#2/25~96.8%Estimated
estimated from related benchmarks
Benchmarks in other categories (4)

Coding benchmarks

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

~#5/14~80.3%Estimated
estimated from related benchmarks
~#2/14~88.2%Estimated
estimated from related benchmarks
~#2/14~85.8%Estimated
estimated from related benchmarks
LiveCodeBench
third-party
~#2/20~92.2%Estimated
estimated from related benchmarks
~#2/20~92.1%Estimated
estimated from related benchmarks
Not comparable across labs (1)

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
~#2/5~90.9%Estimated
estimated from related benchmarks
~#2/5~92.1%Estimated
estimated from related benchmarks
~#2/5~90.4%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

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)