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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.
Claude Opus 5.5Granite 4.2 3BMagistral Small 1.2
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
  • Claude Opus 5.5
    Quality
    99.9
    Rank
    #1/182
    Price
    $8.00/M tok
    Speed
    92tok/s
    In$4.00Out$20/M tok

    vs Magistral Small 1.2: +63.7 quality · 11× price

  • Granite 4.2 3B
    Quality
    23.4
    Rank
    #128/182
    Price
    $0.05/M tok
    Speed
    220tok/s
    In$0.03▾Out$0.12▾/M tok

    vs Claude Opus 5.5: −76.6 quality · 0.01× price

  • Magistral Small 1.2
    Quality
    36.3
    Rank
    #99/182
    Price
    $0.75/M tok
    Speed
    —
    In$0.50Out$1.50/M tok

    vs Claude Opus 5.5: −63.7 quality · 0.09× price

Overview

Lab
Anthropic
IBM Granite
Mistral AI
Released
Sep 22, 2026
Aug 25, 2026
Sep 17, 2025
Weights
Proprietary
Open
Open
Input price
$/M tok
$4.00
$0.03Best
$0.50
Output price
$/M tok
$20
$0.12Best
$1.50
Blended price
$/M tok · 3:1 in:out
$8.00
$0.052Best
$0.75
Output speed
tok/s
92
220Best
—
Context
tokens
1MBest
131K
128K

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.

96.9±3.4Best
#1/103Mixedbest value
17.2±8.0
#95/103Verifiedbest value
Not ranked
93.0±4.3Best
#3/146Verifiedbest value
Not ranked
36.9±9.5
#81/146Verified
94.5±4.8Best
#2/82Verifiedbest value
Not ranked
32.2±8.2
#59/82Verified
99.9±2.6Best
#1/182Verifiedbest value
23.4±3.7
#128/182Verified
36.2±4.3
#99/182Verified
99.6±4.1Best
#1/173Verifiedbest value
17.0±5.8
#140/173Verified
15.9±5.8
#157/173Verified

Hard reasoning 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.

~last/15below measured range (<41.1)Estimated
estimated from related benchmarks
—

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
~#2/5~92.3%Estimated
estimated from related benchmarks
—
~last/5below measured range (<81.3%)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
—
~#2/9~86.1%Estimated
estimated from related benchmarks
—
~last/9below measured range (<74.5%)Estimated
estimated from related benchmarks
~#2/8~91.4%Estimated
estimated from related benchmarks
—
Chartography
third-party
—
~last/23below measured range (<9.0%)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.

~#2/5~58.7%Estimated
estimated from related benchmarks
~last/5below measured range (<47.5%)Estimated
estimated from related benchmarks
~last/5below measured range (<47.5%)Estimated
estimated from related benchmarks
Not comparable across labs (1)