[whatmodel.sh](../../README.md) / Solar Pro 4 # Solar Pro 4 Upstage · released 2026-08 · closed weights **score 63.4** ±1.3 · #164 of 732 · from 3 benchmark results across 1 source Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at ● marks Solar Pro 4 among every model on that task or test, worst to best. 
task            vs the others          rank  counts  tests
agent tasks     ▁▁▃▆█▄●▅▄▄▂▁   #133 of 313*     48%      1
coding          ▁▁▁▃▅▇█▇●▄▃▁   #110 of 469*     33%      1
chat & writing  ▁▁▁▃▆▄▆█▆●▇▃   #128 of 402*     19%      1
agent tasks · #133 of 313 · 48% of its score Beats [o3](o3.md), [Gemini 2.5 Pro](gemini-2-5-pro.md), [Gemini 3.1 Flash-Lite](gemini-3-1-flash-lite.md) here, though they rank higher overall. Trails [SmolLM3 3B](smollm3-3b.md), [Jamba 1.5 Large](jamba-1-5-large.md), [Devstral 2 (2512)](devstral-2.md) here, though they rank lower overall. 
test                                     result  vs the others in its run  difficulty      counts  why
Arena Agent (October 2026 aggrega…  -0.2079 IPS  ●▁▁▃▃▂█▁▂▂▁▁ beats 0/59   avg -0.379 IPS     48%  sharp
coding · #110 of 469 · 33% of its score Beats [Grok 4.3](grok-4-3.md), [Muse Glimmer 30B](muse-glimmer-30b.md), [Qwen3.5 Plus](qwen3-5-plus.md) here, though they rank higher overall. Trails [Llama 3.1 Nemotron Ultra 253B v1](llama-3-1-nemotron-ultra-253b.md) here, though they rank lower overall. 
test                       result  vs the others in its run   difficulty  counts  why
Arena WebDev (Code Arena)  1370.2  ▁▁▃▂●█▃▆▅▅▁▂ beats 36/129  avg 981        33%  sharp
chat & writing · #128 of 402 · 19% of its score Beats [LongCat 2.0 (1.6T-A48B)](longcat-2-0.md), [o3-mini](o3-mini.md), [MiMo-V2-Flash (309B-A15B)](mimo-v2-flash.md) here, though they rank higher overall. Trails [LFM2.5 2.6B](lfm2-5-2-6b.md), [Nemotron-Cascade-8B](nemotron-cascade-8b.md), [DeepSeek V3 0324](deepseek-v3-0324.md) here, though they rank lower overall. 
test            result  vs the others in its run    difficulty  counts  why
LMArena (text)  1387.8  ▁▁▁▂▃▃▃▆▆●█▃ beats 230/385  avg 1260       19%  blunt
## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md) 
source                         results  share of the score
LMArena leaderboard dataset          3   99% ▇▇▇▇▇▇▇▇▇▇▇▇
prior: pull toward the middle             1% ▇
weighted average                        = 63.4
Licences: LMArena leaderboard dataset ([CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)) ## How to run it ### Through an API api (Upstage) · $0.52/M blended · $0.3 in / $1.2 out per 1M tokens · [developers.upstage.ai](https://developers.upstage.ai/docs/apis/chat) [price source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/providers/upstage/models/solar-pro4.toml): Standard base token rate from models.dev. Provider-specific tiers, long-context surcharges, caching and promotions may differ. · [context source](https://github.com/anomalyco/models.dev/blob/a668908cfe7073faa0363699486fc41a3ff52412/models/upstage/solar-pro4.toml) [interactive version](https://whatmodel.sh/model/solar-pro-4) · [JSON](https://whatmodel.sh/api?format=json&all=1)