GPT-5.1-Codex-Mini vs gpt-oss-20b
GPT-5.1-Codex-Mini leads gpt-oss-20b on the Artificial Analysis Intelligence Index, 20.4 to 10.0, and gpt-oss-20b costs 13.3x less per output token ($0.15 vs $2.00 per million). Updated October 21, 2026; 14 benchmarks have a result for both.
GPT-5.1-Codex-Mini or gpt-oss-20b: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.1-Codex-Mini for a larger context window (400K against 131K tokens).
- Shared results
- 14
- GPT-5.1-Codex-Mini only
- 8
- gpt-oss-20b only
- 48
- Like-for-like categories
- 8 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
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini leads, 20.4 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
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini leads, 1111 against 852.
Same board, both measured
Long documents
Listed context window
GPT-5.1-Codex-Mini
GPT-5.1-Codex-Mini takes 400K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-20b
GPT-5.1-Codex-Mini $0.0013, gpt-oss-20b $0.0001 per turn.
List prices
At a glance
- Coding index
- GPT-5.1-Codex-Mini not benchmarked, gpt-oss-20b not benchmarked.
- Widest category
- Coding, 28.9 points apart on average over 3 shared benchmarks.
- Widest single gap
- Terminal-Bench: GPT-5.1-Codex-Mini 61.6% against gpt-oss-20b 3.4%, 58.2 points apart on a 0 to 100 scale.
- Output price
- GPT-5.1-Codex-Mini $2.00 against gpt-oss-20b $0.15 per million output tokens, 13.3x apart.
- Context window
- GPT-5.1-Codex-Mini takes 400K tokens, gpt-oss-20b 131K.
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-5.1-Codex-Mini | Bars | gpt-oss-20b | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 2 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 14 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | GPT-5.1-Codex-Mini | gpt-oss-20b | Leader |
|---|---|---|---|
| LMArena WebDev | 1244 | Not measured | Only GPT-5.1-Codex-Mini measured |
| LiveCodeBench (Vals AI) | Not measured | 80.4% | Only gpt-oss-20b measured |
| LiveCodeBench (Artificial Analysis run) | 83.6% | 77.7% | GPT-5.1-Codex-Mini |
| SciCode | Not measured | 38.9% | Only gpt-oss-20b measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 10.6% | GPT-5.1-Codex-Mini |
| Terminal-Bench | 61.6% | 3.4% | GPT-5.1-Codex-Mini |
| WeirdML | Not measured | 40.9% | Only gpt-oss-20b measured |
| ALE-Bench | Not measured | 566.0 | Only gpt-oss-20b measured |
| LMArena Text: coding | Not measured | 1307 | Only gpt-oss-20b measured |
| LMArena Text: software and IT | Not measured | 1311 | Only gpt-oss-20b measured |
| LMArena WebDev: HTML | 1253 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex-Mini | gpt-oss-20b | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.4 | 10.0 | GPT-5.1-Codex-Mini |
| Epoch Capabilities Index | Not measured | 137.7 | Only gpt-oss-20b measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex-Mini | gpt-oss-20b | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 62.9% | 60.2% | GPT-5.1-Codex-Mini |
| BrowseComp-Plus | Not measured | 50.6% | 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 index20
| Benchmark | GPT-5.1-Codex-Mini | gpt-oss-20b | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 68.9% | Only gpt-oss-20b measured |
| GPQA Diamond (Artificial Analysis run) | 81.3% | 68.8% | GPT-5.1-Codex-Mini |
| Humanity's Last Exam (Artificial Analysis run) | 18.5% | 11.0% | GPT-5.1-Codex-Mini |
| GPQA Diamond (Epoch AI run) | Not measured | 60.8% | Only gpt-oss-20b measured |
| LMArena Text: hard prompts | Not measured | 1274 | Only gpt-oss-20b measured |
| LMArena Text: expert | Not measured | 1258 | Only gpt-oss-20b measured |
| LMArena Text: hard prompts in English | Not measured | 1292 | Only gpt-oss-20b measured |
| Kagi LLM Benchmark | Not measured | 53.2% | Only gpt-oss-20b measured |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex-Mini | gpt-oss-20b | Leader |
|---|---|---|---|
| AIME | Not measured | 86.0% | Only gpt-oss-20b measured |
| MATH 500 (Vals AI) | Not measured | 94.2% | Only gpt-oss-20b measured |
| MGSM (Vals AI) | Not measured | 89.0% | Only gpt-oss-20b measured |
| AA Math Index | 91.7 | 89.3 | GPT-5.1-Codex-Mini |
| AIME 2025 (Artificial Analysis run) | 91.7% | 89.3% | GPT-5.1-Codex-Mini |
| OTIS Mock AIME | Not measured | 65.3% | Only gpt-oss-20b measured |
| LMArena Text: math | Not measured | 1317 | Only gpt-oss-20b measured |
| LMArena Text: mathematical work | Not measured | 1305 | Only gpt-oss-20b measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.1-Codex-Mini | gpt-oss-20b | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 71.6% | Only gpt-oss-20b measured |
| LegalBench (Vals AI) | Not measured | 70.8% | Only gpt-oss-20b measured |
| CaseLaw (Vals AI) | Not measured | 43.8% | Only gpt-oss-20b measured |
| CorpFin (Vals AI) | Not measured | 53.1% | Only gpt-oss-20b measured |
| TaxEval (Vals AI) | Not measured | 63.7% | Only gpt-oss-20b measured |
| MedQA (Vals AI) | Not measured | 82.9% | Only gpt-oss-20b measured |
| MMLU Pro (Artificial Analysis run) | 82.0% | 74.8% | GPT-5.1-Codex-Mini |
| LMArena Text: science | Not measured | 1296 | Only gpt-oss-20b measured |
| LMArena Text: medicine and healthcare | Not measured | 1310 | Only gpt-oss-20b measured |
| LMArena Text: legal and government | Not measured | 1280 | Only gpt-oss-20b measured |
| LMArena Text: business and finance | Not measured | 1284 | 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 index20
| Benchmark | GPT-5.1-Codex-Mini | gpt-oss-20b | Leader |
|---|---|---|---|
| Design Arena: websites | 1111 | 852 | GPT-5.1-Codex-Mini |
| Design Arena: UI components | 1081 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: game dev | 1092 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: data viz | 1097 | 933 | GPT-5.1-Codex-Mini |
| Design Arena: 3D | 988 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: all code categories | 1094 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: SVG | 978 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Design Arena: ASCII art | 1105 | Not measured | Only GPT-5.1-Codex-Mini measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.1-Codex-Mini | gpt-oss-20b | Leader |
|---|---|---|---|
| IFBench | 67.9% | 65.1% | GPT-5.1-Codex-Mini |
| Long context reasoning (AA-LCR) | 66.7% | 34.7% | GPT-5.1-Codex-Mini |
| DTBench | Not measured | 68.0% | Only gpt-oss-20b measured |
| LMCA | Not measured | 14.5% | Only gpt-oss-20b measured |
| LMArena Text | Not measured | 1288 | Only gpt-oss-20b measured |
| LMArena Text: instruction following | Not measured | 1236 | Only gpt-oss-20b measured |
| LMArena Text: creative writing | Not measured | 1201 | Only gpt-oss-20b measured |
| LMArena Text: English | Not measured | 1303 | Only gpt-oss-20b measured |
| LMArena Text: non-English | Not measured | 1269 | Only gpt-oss-20b measured |
| LMArena Text: Chinese | Not measured | 1315 | Only gpt-oss-20b measured |
| LMArena Text: German | Not measured | 1255 | Only gpt-oss-20b measured |
| LMArena Text: Japanese | Not measured | 1244 | Only gpt-oss-20b measured |
| LMArena Text: Korean | Not measured | 1236 | Only gpt-oss-20b measured |
| LMArena Text: Spanish | Not measured | 1267 | Only gpt-oss-20b measured |
| LMArena Text: Russian | Not measured | 1278 | Only gpt-oss-20b measured |
| LMArena Text: Polish | Not measured | 1252 | Only gpt-oss-20b measured |
| LMArena Text: multi-turn | Not measured | 1268 | Only gpt-oss-20b measured |
| LMArena Text: longer queries | Not measured | 1250 | Only gpt-oss-20b measured |
| LMArena Text: writing and language | Not measured | 1238 | Only gpt-oss-20b measured |
| LMArena Text: entertainment and media | Not measured | 1216 | 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-5.1-Codex-Mini | gpt-oss-20b | 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-5.1-Codex-Mini | OpenAI gpt-oss-20b |
|---|---|---|
| Maker | OpenAI | OpenAI |
| Weights | No public weights listed | Open weights |
| Released | November 13, 2025 | August 5, 2025 |
| Context window | 400K | 131K |
| Input $/Mtok | $0.25 | $0.03 |
| Output $/Mtok | $2.00 | $0.15 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.1-Codex-Mini better than gpt-oss-20b for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.1-Codex-Mini for a larger context window (400K against 131K tokens).
Which is cheaper, GPT-5.1-Codex-Mini or gpt-oss-20b?
GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2.00 per million output tokens; gpt-oss-20b costs $0.03 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-5.1-Codex-Mini or gpt-oss-20b?
GPT-5.1-Codex-Mini, with 400K tokens against 131K.
How many benchmarks is the GPT-5.1-Codex-Mini vs gpt-oss-20b comparison based on?
14 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex-Mini's coding index rests on 1 independent benchmark and gpt-oss-20b's on 0. Where only one model has a result, the page says so instead of naming a winner.