gpt-oss-20b vs Solar Mini 4
Solar Mini 4 leads gpt-oss-20b on the Artificial Analysis Intelligence Index, 24.1 to 10.0, and gpt-oss-20b costs 1.3x less per output token ($0.15 vs $0.20 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
gpt-oss-20b or Solar Mini 4: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick gpt-oss-20b for output tokens 1.3x cheaper ($0.15 vs $0.20 per million) and work measured by SciCode or AA Intelligence Index, where it leads.
- Shared results
- 5
- gpt-oss-20b only
- 57
- Solar Mini 4 only
- 2
- Like-for-like categories
- 5 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Solar Mini 4
Solar Mini 4 leads, 24.1 against 10.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only gpt-oss-20b has a GPQA Diamond result, 68.9%.
Directional only
Math
AIME
No call
Only gpt-oss-20b has a AIME result, 86.0%.
Directional only
Knowledge
MMLU Pro
No call
Only gpt-oss-20b has a MMLU Pro result, 71.6%.
Directional only
Web design
Design Arena: websites
Solar Mini 4
Solar Mini 4 leads, 1158 against 852.
Same board, both measured
Long documents
Listed context window
Solar Mini 4
Solar Mini 4 takes 524K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-20b
gpt-oss-20b $0.0001, Solar Mini 4 $0.0001 per turn.
List prices
At a glance
- Coding index
- gpt-oss-20b not benchmarked, Solar Mini 4 not benchmarked.
- Widest category
- General, 48.7 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): gpt-oss-20b 34.7% against Solar Mini 4 83.3%, 48.7 points apart on a 0 to 100 scale.
- Output price
- gpt-oss-20b $0.15 against Solar Mini 4 $0.20 per million output tokens, 1.3x apart.
- Context window
- gpt-oss-20b takes 131K tokens, Solar Mini 4 524K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | gpt-oss-20b | Bars | Solar Mini 4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| Web design | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | gpt-oss-20b | Solar Mini 4 | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 80.4% | Not measured | Only gpt-oss-20b measured |
| LiveCodeBench (Artificial Analysis run) | 77.7% | Not measured | Only gpt-oss-20b measured |
| SciCode | 38.9% | 47.6% | Solar Mini 4 |
| Terminal-Bench Hard (Artificial Analysis run) | 10.6% | Not measured | Only gpt-oss-20b measured |
| Terminal-Bench | 3.4% | Not measured | Only gpt-oss-20b measured |
| WeirdML | 40.9% | Not measured | Only gpt-oss-20b measured |
| ALE-Bench | 566.0 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: coding | 1307 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: software and IT | 1311 | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-20b | Solar Mini 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.0 | 24.1 | Solar Mini 4 |
| Epoch Capabilities Index | 137.7 | Not measured | Only gpt-oss-20b measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | gpt-oss-20b | Solar Mini 4 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 60.2% | Not measured | Only gpt-oss-20b measured |
| BrowseComp-Plus | 50.6% | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-20b | Solar Mini 4 | Leader |
|---|---|---|---|
| GPQA Diamond | 68.9% | Not measured | Only gpt-oss-20b measured |
| GPQA Diamond (Artificial Analysis run) | 68.8% | Not measured | Only gpt-oss-20b measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.0% | 25.8% | Solar Mini 4 |
| GPQA Diamond (Epoch AI run) | 60.8% | Not measured | Only gpt-oss-20b measured |
| LMArena Text: hard prompts | 1274 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: expert | 1258 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: hard prompts in English | 1292 | Not measured | Only gpt-oss-20b measured |
| Kagi LLM Benchmark | 53.2% | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | gpt-oss-20b | Solar Mini 4 | Leader |
|---|---|---|---|
| AIME | 86.0% | Not measured | Only gpt-oss-20b measured |
| MATH 500 (Vals AI) | 94.2% | Not measured | Only gpt-oss-20b measured |
| MGSM (Vals AI) | 89.0% | Not measured | Only gpt-oss-20b measured |
| AA Math Index | 89.3 | Not measured | Only gpt-oss-20b measured |
| AIME 2025 (Artificial Analysis run) | 89.3% | Not measured | Only gpt-oss-20b measured |
| OTIS Mock AIME | 65.3% | Not measured | Only gpt-oss-20b measured |
| LMArena Text: math | 1317 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: mathematical work | 1305 | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | gpt-oss-20b | Solar Mini 4 | Leader |
|---|---|---|---|
| MMLU Pro | 71.6% | Not measured | Only gpt-oss-20b measured |
| LegalBench (Vals AI) | 70.8% | Not measured | Only gpt-oss-20b measured |
| CaseLaw (Vals AI) | 43.8% | Not measured | Only gpt-oss-20b measured |
| CorpFin (Vals AI) | 53.1% | Not measured | Only gpt-oss-20b measured |
| TaxEval (Vals AI) | 63.7% | Not measured | Only gpt-oss-20b measured |
| MedQA (Vals AI) | 82.9% | Not measured | Only gpt-oss-20b measured |
| MMLU Pro (Artificial Analysis run) | 74.8% | Not measured | Only gpt-oss-20b measured |
| LMArena Text: science | 1296 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: medicine and healthcare | 1310 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: legal and government | 1280 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: business and finance | 1284 | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-20b | Solar Mini 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 852 | 1158 | Solar Mini 4 |
| Design Arena: game dev | Not measured | 1106 | Only Solar Mini 4 measured |
| Design Arena: data viz | 933 | Not measured | Only gpt-oss-20b measured |
| Design Arena: all code categories | Not measured | 1150 | Only Solar Mini 4 measured |
| Neither model has a result on the other 5 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | gpt-oss-20b | Solar Mini 4 | Leader |
|---|---|---|---|
| IFBench | 65.1% | Not measured | Only gpt-oss-20b measured |
| Long context reasoning (AA-LCR) | 34.7% | 83.3% | Solar Mini 4 |
| DTBench | 68.0% | Not measured | Only gpt-oss-20b measured |
| LMCA | 14.5% | Not measured | Only gpt-oss-20b measured |
| LMArena Text | 1288 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: instruction following | 1236 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: creative writing | 1201 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: English | 1303 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: non-English | 1269 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: Chinese | 1315 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: German | 1255 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: Japanese | 1244 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: Korean | 1236 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: Spanish | 1267 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: Russian | 1278 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: Polish | 1252 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: multi-turn | 1268 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: longer queries | 1250 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: writing and language | 1238 | Not measured | Only gpt-oss-20b measured |
| LMArena Text: entertainment and media | 1216 | Not measured | Only gpt-oss-20b measured |
| Neither model has a result on the other 26 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | gpt-oss-20b | Solar Mini 4 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
gpt-oss-20b costs less
Repository review
50K input + 3K output tokens
gpt-oss-20b costs less
Agent loop
200K input + 10K output tokens
gpt-oss-20b costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI gpt-oss-20b | Upstage Solar Mini 4 |
|---|---|---|
| Maker | OpenAI | Upstage |
| Weights | Open weights | No public weights listed |
| Released | August 5, 2025 | September 23, 2026 |
| Context window | 131K | 524K |
| Input $/Mtok | $0.03 | $0.05 |
| Output $/Mtok | $0.15 | $0.20 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is gpt-oss-20b better than Solar Mini 4 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick gpt-oss-20b for output tokens 1.3x cheaper ($0.15 vs $0.20 per million) and work measured by SciCode or AA Intelligence Index, where it leads.
Which is cheaper, gpt-oss-20b or Solar Mini 4?
gpt-oss-20b costs $0.03 per million input tokens and $0.15 per million output tokens; Solar Mini 4 costs $0.05 and $0.20. Cost per solved task is known for neither of them.
Which has the bigger context window, gpt-oss-20b or Solar Mini 4?
Solar Mini 4, with 524K tokens against 131K.
How many benchmarks is the gpt-oss-20b vs Solar Mini 4 comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. gpt-oss-20b's coding index rests on 0 independent benchmarks and Solar Mini 4's on 0. Where only one model has a result, the page says so instead of naming a winner.