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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.
Xing4.0-29B-A4BQwen3.8-Omni-FlashQwen3.8 Flash-Next
Focus

Writing & chat: quality vs price

Compared models are ringed; the other 143 ranked here are greyed.

Lower price is better. Pareto frontier: Gemma 4 E4B, Qwen3.5 4B, Gemma 4 12B, Qwen3.5 9B, Gemma 4 26B A4B, GPT-6 Luna, Qwen3.8 Flash-Next, MiMo-V2.6-Pro, Step 5 Preview, GLM-5.3, Kimi K3, Claude Opus 5.5, Claude Opus 5, Claude Fable 5.1. 52 models are not plotted: Intern-S2-Preview (35B-A3B), Xing4.0-29B-A4B, Nex-N2-Pro, Nemotron Cascade 2 30B A3B, Apriel-v1.6-15B-Thinker, Command A+, EXAONE 4.5 33B, HyperNova 60B 2605, DiffusionGemma 26B A4B, K2 Think V2, K2-V2, Solar Open 100B, Step3 VL 10B, Tri-21B-Think, Falcon-H1R-7B, North Mini Code, NVIDIA Nemotron 3 Nano 4B, LFM2.5-8B-A1B, LongCat Flash Lite, MiniCPM5-1B, Jamba Reasoning 3B, LFM2 24B A2B, Nanbeige4.1-3B, HyperCLOVA X SEED Think (32B), INTELLECT-3, Olmo 3 7B Think, LFM2.5-1.2B-Instruct, Llama 3.1 Nemotron Ultra 253B v1, LFM2.5-1.2B-Thinking, Devstral 2, Olmo 3.1 32B Instruct, Olmo 3.1 32B Think, Gemma 4 E2B, Qwen3.5 2B, EXAONE 4.0 32B, Devstral Small 2, Jamba 1.7 Large, MiniCPM-V 4.6 1.3B, LFM2.5-VL-1.6B, Hermes 4 - Llama-3.1 70B, Molmo2-8B, Jamba 1.7 Mini, Kimi Linear 48B A3B Instruct, Exaone 4.0 1.2B, Granite 4.0 H 1B, Granite 4.0 Micro, Qwen3.5 0.8B, Molmo 7B-D, Tiny Aya Global, Granite 4.0 H 350M, Granite 4.0 350M, Gemma 3 270M.

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

Intern-S2-Preview (35B-A3B), Xing4.0-29B-A4B, Nex-N2-Pro, Nemotron Cascade 2 30B A3B, Apriel-v1.6-15B-Thinker, Command A+, EXAONE 4.5 33B, HyperNova 60B 2605, DiffusionGemma 26B A4B, K2 Think V2, K2-V2, Solar Open 100B, Step3 VL 10B, Tri-21B-Think, Falcon-H1R-7B, North Mini Code, NVIDIA Nemotron 3 Nano 4B, LFM2.5-8B-A1B, LongCat Flash Lite, MiniCPM5-1B, Jamba Reasoning 3B, LFM2 24B A2B, Nanbeige4.1-3B, HyperCLOVA X SEED Think (32B), INTELLECT-3, Olmo 3 7B Think, LFM2.5-1.2B-Instruct, Llama 3.1 Nemotron Ultra 253B v1, LFM2.5-1.2B-Thinking, Devstral 2, Olmo 3.1 32B Instruct, Olmo 3.1 32B Think, Gemma 4 E2B, Qwen3.5 2B, EXAONE 4.0 32B, Devstral Small 2, Jamba 1.7 Large, MiniCPM-V 4.6 1.3B, LFM2.5-VL-1.6B, Hermes 4 - Llama-3.1 70B, Molmo2-8B, Jamba 1.7 Mini, Kimi Linear 48B A3B Instruct, Exaone 4.0 1.2B, Granite 4.0 H 1B, Granite 4.0 Micro, Qwen3.5 0.8B, Molmo 7B-D, Tiny Aya Global, Granite 4.0 H 350M, Granite 4.0 350M, Gemma 3 270M

  • Best-value frontier (nothing is both cheaper and better)
  • Evidencestrong → weak
  • Estimated from other categories
  • Xing4.0-29B-A4B
    Quality
    67.4
    Rank
    #32/146
    Price
    —
    Speed
    —

    vs Qwen3.8 Flash-Next: −12.6 quality · price n/a

  • Qwen3.8-Omni-Flash
    Quality
    78.8
    Rank
    #13/146
    Price
    $0.23/M tok
    Speed
    —
    In$0.15▾Out$0.47▾/M tok

    vs Qwen3.8 Flash-Next: −1.2 quality · 1× price

  • Qwen3.8 Flash-Next
    Quality
    80.0
    Rank
    #12/146
    Price
    $0.23/M tok
    Speed
    54tok/s
    In$0.15▾Out$0.47▾/M tok

    vs Qwen3.8-Omni-Flash: +1.2 quality · 1× price

Overview

Lab
China Telecom AI (TeleAI)
Alibaba Qwen
Alibaba Qwen
Released
Sep 17, 2026
Sep 18, 2026
Aug 26, 2026
Weights
Open
Proprietary
Open
Input price
$/M tok
—
$0.15Best
$0.15Best
Output price
$/M tok
—
$0.47Best
$0.47Best
Blended price
$/M tok · 3:1 in:out
—
$0.23Best
$0.23Best
Output speed
tok/s
—
—
54
Context
tokens
262K
1MBest
262K

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.

62.1±10.6
#19/103Lab-reported
63.1±8.6Best
#18/103Lab-reported
62.0±5.2
#20/103Mixed
67.4±9.7
#32/146Lab-reported
78.8±9.7
#13/146Lab-reported
80.0±9.7Best
#12/146Lab-reportedbest value
Not ranked
78.6±10.2Best
#7/82Lab-reportedbest value
72.6±5.3
#16/82Mixed
59.8±10.0
#46/182Lab-reported
73.5±6.6
#27/182Lab-reported
76.0±3.7Best
#24/182Verifiedbest value
Not ranked
Not ranked
81.7±5.8
#14/173Verifiedbest value

Writing & chat 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)

Coding 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)

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
—

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
Not comparable across labs (1)