[whatmodel.sh](../../README.md) / Solar Open 2 (250B-A15B) # Solar Open 2 (250B-A15B) Upstage · released 2026-07 · 250.29B params (15B active) · upstage-solar-license **score 70.5** ±1.2 · #75 of 732 · from 13 benchmark results across 1 source · † no independently run results verified Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at ● marks Solar Open 2 (250B-A15B) among every model on that task or test, worst to best. 
task         vs the others         rank  counts  tests
agent tasks  ▁▁▃▆█▄▅▅●▄▂▁    #75 of 313     29%      5
coding       ▁▁▁▃▅▇█▇▅●▃▁   #67 of 469*    8.4%      2
math         ▁▁▃▅█▆▄█●▂▁▁   #66 of 431*     11%      2
agent tasks · #75 of 313 · 29% of its score Beats [GPT-5 Pro](gpt-5-pro.md), [GPT-5](gpt-5.md), [Gemini 3 Flash (Preview)](gemini-3-flash-preview.md) here, though they rank higher overall. Trails [MiMo-V2.5 (310B-A15B)](mimo-v2-5.md), [MiniMax-M3](minimax-m3.md), [Qwen3.5 397B-A17B](qwen3-5-397b-a17b.md) here, though they rank lower overall. 
test                            result  vs the others in its run  difficulty            counts  why
Terminal-Bench Hard (maker)      28.3%  ▄········●█▄ beats 2/5    very hard · avg 4.6%    9.3%  sharp · at its level
APEX-Agents (pass@1) (maker)     16.6%  ▄▄····▄···█● beats 5/5    very hard · avg 1.9%    8.8%  typical
MCP-Atlas (public set) (maker)   58.2%  ▄▄▄·······●▄ beats 3/5    hard · avg 19%          5.1%  at its level
SWE-bench Verified (maker)       70.4%  ▄··········● beats 3/5    hard · avg 15%          3.8%  sharp · at its level · noisy
τ³-bench Banking (maker)         19.6%  █·▄▄······●▄ beats 4/5    very hard · avg 5.3%    2.0%  blunt
coding · #67 of 469 · 8.4% of its score Beats [Gemini 3.1 Pro (Preview)](gemini-3-1-pro.md), [DeepSeek V4 Flash Vision (Exp)](deepseek-v4-flash-vision-exp.md), [GPT-5.2](gpt-5-2.md) here, though they rank higher overall. Trails [MiMo-V2.5-Pro (1T-A42B)](mimo-v2-5-pro.md), [MiniMax-M3](minimax-m3.md), [Ornith 1.5 35B-A3B](ornith-1-5-35b-a3b.md) here, though they rank lower overall. 
test                                result  vs the others in its run  difficulty        counts  why
LiveCodeBench v6 (window unspecif…   92.4%  ▄······▄▄▄·● beats 5/5    medium · avg 50%    4.6%  typical
SWE-bench Verified (maker)           70.4%  ▄··········● beats 3/5    hard · avg 15%      3.8%  sharp · at its level · noisy
math · #66 of 431 · 11% of its score Beats [Qwen3.6 Max Preview](qwen3-6-max-preview.md), [Claude Sonnet 4.6](claude-sonnet-4-6.md), [Claude Opus 4.5](claude-opus-4-5.md) here, though they rank higher overall. Trails [INTELLECT-3](intellect-3.md), [GPT-5 mini](gpt-5-mini.md), [Qwen3-Coder-Next (80B-A3B)](qwen3-coder-next.md) here, though they rank lower overall. 
test                        result  vs the others in its run  difficulty        counts  why
AIME 2026 (maker)            95.7%  ▄▄··▄····●·▄ beats 3/5    medium · avg 65%    7.1%  sharp · maxed out
HMMT February 2026 (maker)   93.9%  █▄▄········● beats 4/5    hard · avg 31%      4.0%  sharp · noisy
other tests (5) 
test                                result  vs the others in its run  difficulty            counts  why
GPQA Diamond (maker)                 86.3%  █···██·█··●█ beats 4/5    hard · avg 41%           23%  sharp
Humanity's Last Exam (maker)         28.8%  █▄······▄·●▄ beats 4/5    very hard · avg 4.7%     14%  at its level
MMLU-Pro (maker)                     86.2%  ▄·▄▄····▄··● beats 5/5    medium · avg 55%        7.7%  typical
IFBench (aggregation unspecified)…   80.0%  ▄···▄▄··▄··● beats 4/5    medium · avg 43%        5.6%  typical
MultiChallenge (maker)               61.0%  █··▄·▄·····● beats 4/5    hard · avg 25%          5.1%  at its level
## 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
Solar Open 2 Technical Report (submitte…       13   99% ▇▇▇▇▇▇▇▇▇▇▇▇
prior: pull toward the middle                        1% ▇
weighted average                                   = 70.5
Licences: Solar Open 2 Technical Report ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) ## How to run it ### Other ways to run it 1. Run it as published (BF16, needs ~500.58 GB, NVIDIA only, from [huggingface.co/upstage](https://huggingface.co/upstage/Solar-Open2-250B/tree/9190fbe63a2ad8e17fc766ccceb36de7c66f004b)) ```sh vllm serve upstage/Solar-Open2-250B --served-model-name solar-open2-250b --tensor-parallel-size 8 --enable-expert-parallel --moe-backend triton --default-chat-template-kwargs '{"think_render_option":"preserved"}' --reasoning-parser solar_open2 --tool-call-parser solar_open2 --enable-auto-tool-choice --logits-processors vllm.v1.sample.logits_processor.solar_open2:SolarOpen2TemplateLogitsProcessor ``` Model repository and documentation: [huggingface.co/upstage](https://huggingface.co/upstage/Solar-Open2-250B) [interactive version](https://whatmodel.sh/model/solar-open-2) · [JSON](https://whatmodel.sh/api?format=json&all=1)