[whatmodel.sh](../../README.md) / Solar Open 100B (102B-A12B)
# Solar Open 100B (102B-A12B)
Upstage · released 2025-12 · 102.6B params (12B active) · upstage-solar-license
**score 59.4** ±1.1 · #213 of 732 · from 14 benchmark results across 2 sources · † 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 100B (102B-A12B) among every model on that task or test, worst to best.
task vs the others rank counts tests
agent tasks ▁▁▃▆█●▅▅▄▄▂▁ #183 of 313 20% 6
coding ▁▁▁▃▅●█▇▅▄▃▁ #326 of 469* 9.4% 2
math ▁▁▃▅█▆●█▄▂▁▁ #182 of 431* 19% 2
agent tasks · #183 of 313 · 20% of its score
Beats [o1 (2024-12-17)](o1-2024-12-17.md), [o3-mini](o3-mini.md), [DeepSeek R1 0528](deepseek-r1-0528.md) here, though they rank higher overall. Trails [SmolLM3 3B](smollm3-3b.md), [Jamba 1.5 Mini](jamba-1-5-mini.md), [Jamba 1.5 Large](jamba-1-5-large.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
τ²-bench Telecom (maker) 55.6% ▁·▅█▆●▂▃▃▂▃▁ beats 46/89 very hard · avg 15% 5.3% sharp · at its level · noisy · small run
Terminal-Bench Hard (maker) 2.3% ●········██▄ beats 0/5 very hard · avg 4.6% 3.8% sharp
MCP-Atlas (public set) (maker) 34.4% ▄▄●·······█▄ beats 2/5 hard · avg 19% 3.6% at its level
APEX-Agents (pass@1) (maker) 2.4% ▄●····▄···█▄ beats 1/5 very hard · avg 1.9% 3.1% too hard for it
SWE-bench Verified (maker) 15.4% ●··········█ beats 1/5 hard · avg 15% 3.0% sharp · at its level · noisy
τ³-bench Banking (maker) 7.4% █·●▄······▄▄ beats 2/5 very hard · avg 5.3% 1.0% blunt
coding · #326 of 469 · 9.4% of its score
Trails [DeepSeek LLM 67B Chat](deepseek-llm-67b-chat.md), [WizardLM 70B V1.0](wizardlm-70b-v1-0.md), [Llama 3.2 11B Vision Instruct](llama-3-2-11b-vision.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
LiveCodeBench v6 (window unspecif… 56.5% ●······▄▄▄·█ beats 0/5 medium · avg 50% 6.4% at its level
SWE-bench Verified (maker) 15.4% ●··········█ beats 1/5 hard · avg 15% 3.0% sharp · at its level · noisy
math · #182 of 431 · 19% of its score
Beats [MiniMax-M2.1](minimax-m2-1.md), [Mistral Medium 3.5 (128B)](mistral-medium-3-5.md), [GPT-4.1](gpt-4-1.md) here, though they rank higher overall. Trails [Phi-4-mini-reasoning 3.8B](phi-4-mini-reasoning.md), [OpenThinker3 7B](openthinker3-7b.md), [Olmo 3 7B Think](olmo-3-7b-think.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
AIME 2026 (maker) 87.7% ●▄··▄····█·▄ beats 0/5 medium · avg 65% 14% sharp
HMMT February 2026 (maker) 68.9% █●▄········█ beats 2/5 hard · avg 31% 5.4% sharp · at its level · noisy
other tests (5)
test result vs the others in its run difficulty counts why
GPQA Diamond (maker) 66.2% ●···██·█··██ beats 0/5 hard · avg 41% 29% sharp · at its level
MMLU-Pro (maker) 80.4% ▄·●▄····▄··█ beats 1/5 medium · avg 55% 10% at its level
Humanity's Last Exam (maker) 11.5% ●▄······▄·▄▄ beats 1/5 very hard · avg 4.7% 5.7% typical
IFBench (aggregation unspecified)… 57.7% ●···▄▄··▄··█ beats 0/5 medium · avg 43% 5.5% at its level
MultiChallenge (maker) 40.5% ●··▄·▄·····█ beats 1/5 hard · avg 25% 3.8% at its level
source results share of the score
Solar Open 2 Technical Report (submitte… 13 94% ▇▇▇▇▇▇▇▇▇▇▇
Solar Open Technical Report (submitted … 1 5% ▇
prior: pull toward the middle 1% ▇
weighted average = 59.4
Licences: Solar Open 2 Technical Report ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)) · Solar Open Technical Report ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/))
## How to run it
### llama.cpp (recommended)
1. Install llama.cpp. Homebrew and winget installs name the commands llama-cli and llama-server instead. [Other ways to install](https://github.com/ggml-org/llama.cpp/blob/master/docs/install.md)
```sh
# macOS / Linux
curl -LsSf https://llama.app/install.sh | sh
# Windows
irm https://llama.app/install.ps1 | iex
```
2. Run Solar Open 100B (102B-A12B) (Q4_K_M, needs ~62.3 GB, from [huggingface.co/AaryanK](https://huggingface.co/AaryanK/Solar-Open-100B-GGUF/tree/cfe3fc26a5bfa6401071c97126130bfd25d5ace5))
```sh
llama cli -hf AaryanK/Solar-Open-100B-GGUF:q4_k_m
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf AaryanK/Solar-Open-100B-GGUF:q4_k_m
```
Other versions: Q8_0 (~109.2 GB) `llama cli -hf AaryanK/Solar-Open-100B-GGUF:q8_0` · Q2_K (~37.7 GB) `llama cli -hf AaryanK/Solar-Open-100B-GGUF:q2_k`
### LM Studio
1. Install LM Studio. Open the app once before using the lms command. [Download it (macOS / Windows / Linux)](https://lmstudio.ai/download)
2. Run Solar Open 100B (102B-A12B) (Q4_K_M, needs ~62.3 GB, from [huggingface.co/AaryanK](https://huggingface.co/AaryanK/Solar-Open-100B-GGUF/tree/cfe3fc26a5bfa6401071c97126130bfd25d5ace5))
```sh
lms get https://huggingface.co/AaryanK/Solar-Open-100B-GGUF@q4_k_m -y
```
3. Then run lms ls to see its name, and lms chat followed by that name
Other versions: Q8_0 (~109.2 GB) `lms get https://huggingface.co/AaryanK/Solar-Open-100B-GGUF@q8_0 -y` · Q2_K (~37.7 GB) `lms get https://huggingface.co/AaryanK/Solar-Open-100B-GGUF@q2_k -y` · 4bit (~57.8 GB, Mac only) `lms get https://huggingface.co/mlx-community/Solar-Open-100B-4bit -y` · 8bit (~109.1 GB, Mac only) `lms get https://huggingface.co/mlx-community/Solar-Open-100B-8bit -y`
### Ollama
1. Install Ollama. [Download it (macOS / Windows)](https://ollama.com/download)
```sh
# Linux
curl -fsSL https://ollama.com/install.sh | sh
```
2. Run Solar Open 100B (102B-A12B) (Q2_K, needs ~37.7 GB, from [huggingface.co/AaryanK](https://huggingface.co/AaryanK/Solar-Open-100B-GGUF/tree/cfe3fc26a5bfa6401071c97126130bfd25d5ace5))
```sh
ollama run hf.co/AaryanK/Solar-Open-100B-GGUF:q2_k
```
### MLX (Mac)
1. Install MLX (Mac). Apple silicon Macs only, text only.
```sh
# with uv
uv tool install mlx-lm
# or
pip install mlx-lm
```
2. Run Solar Open 100B (102B-A12B) (4bit, needs ~57.8 GB, Mac only, from [huggingface.co/mlx-community](https://huggingface.co/mlx-community/Solar-Open-100B-4bit/tree/3a1944e955dc1dc8e03354929189e5ad9ee9f895))
```sh
mlx_lm.chat --model mlx-community/Solar-Open-100B-4bit
```
3. Or start an OpenAI-compatible server at http://localhost:8080/v1
```sh
mlx_lm.server --model mlx-community/Solar-Open-100B-4bit
```
Other versions: 8bit (~109.1 GB, Mac only) `mlx_lm.chat --model mlx-community/Solar-Open-100B-8bit`
### Other ways to run it
1. Run it as published (BF16, needs ~205.31 GB, NVIDIA only, from [huggingface.co/upstage](https://huggingface.co/upstage/Solar-Open-100B/tree/1f591439b14055004d1a5d1a975608953a022fea))
```sh
vllm serve upstage/Solar-Open-100B --trust-remote-code --enable-auto-tool-choice --tool-call-parser solar_open --reasoning-parser solar_open --logits-processors vllm.model_executor.models.parallel_tool_call_logits_processor:ParallelToolCallLogitsProcessor --logits-processors vllm.model_executor.models.solar_open_logits_processor:SolarOpenTemplateLogitsProcessor --tensor-parallel-size 8
```
Model repository and documentation: [huggingface.co/upstage](https://huggingface.co/upstage/Solar-Open-100B)
[interactive version](https://whatmodel.sh/model/solar-open-100b) · [JSON](https://whatmodel.sh/api?format=json&all=1)