Gemini 2.5 Flash Lite vs gpt-oss-20b
Gemini 2.5 Flash Lite leads gpt-oss-20b on the Artificial Analysis Intelligence Index, 10.4 to 10.0, and gpt-oss-20b costs 2.7x less per output token ($0.15 vs $0.40 per million). Updated October 21, 2026; 24 benchmarks have a result for both.
Gemini 2.5 Flash Lite or gpt-oss-20b: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemini 2.5 Flash Lite for a larger context window (1.05M against 131K tokens) and work measured by LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
- Shared results
- 24
- Gemini 2.5 Flash Lite only
- 6
- gpt-oss-20b only
- 38
- Like-for-like categories
- 7 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
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite leads, 10.4 against 10.0.
Same board, both measured
Reasoning
GPQA Diamond
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite leads, 70.2% against 68.9%.
Same board, both measured
Math
AIME
gpt-oss-20b
gpt-oss-20b leads, 86.0% against 42.1%.
Same board, both measured
Knowledge
MMLU Pro
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite leads, 79.1% against 71.6%.
Same board, both measured
Web design
Design Arena: websites
No call
Only gpt-oss-20b has a Design Arena: websites result, 852.
Directional only
Long documents
Listed context window
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
gpt-oss-20b
Gemini 2.5 Flash Lite $0.0003, gpt-oss-20b $0.0001 per turn.
List prices
At a glance
- Coding index
- Gemini 2.5 Flash Lite not benchmarked, gpt-oss-20b not benchmarked.
- Widest category
- Agentic work, 41.2 points apart on average over 1 shared benchmark.
- Widest single gap
- AIME: Gemini 2.5 Flash Lite 42.1% against gpt-oss-20b 86.0%, 44.0 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash Lite $0.40 against gpt-oss-20b $0.15 per million output tokens, 2.7x apart.
- Context window
- Gemini 2.5 Flash Lite takes 1.05M 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 | Gemini 2.5 Flash Lite | Bars | gpt-oss-20b | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 3 | ||
| Math | 1 | 3 | ||
| Knowledge | 6 | 0 | ||
| General | 2 | 2 | ||
| All shared boards | 11 | 13 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-20b | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 71.4% | 80.4% | gpt-oss-20b |
| LiveCodeBench (Artificial Analysis run) | 59.3% | 77.7% | gpt-oss-20b |
| SciCode | Not measured | 38.9% | Only gpt-oss-20b measured |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | 10.6% | gpt-oss-20b |
| Terminal-Bench | Not measured | 3.4% | Only gpt-oss-20b measured |
| 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 |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-20b | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.4 | 10.0 | Gemini 2.5 Flash Lite |
| Epoch Capabilities Index | 133.8 | 137.7 | gpt-oss-20b |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-20b | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 19.0% | 60.2% | gpt-oss-20b |
| Berkeley Function Calling Leaderboard (BFCL) | 36.9% | Not measured | Only Gemini 2.5 Flash Lite measured |
| BrowseComp-Plus | Not measured | 50.6% | Only gpt-oss-20b measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-20b | Leader |
|---|---|---|---|
| GPQA Diamond | 70.2% | 68.9% | Gemini 2.5 Flash Lite |
| MMMU Pro (Vals AI) | 75.4% | Not measured | Only Gemini 2.5 Flash Lite measured |
| GPQA Diamond (Artificial Analysis run) | 62.5% | 68.8% | gpt-oss-20b |
| Humanity's Last Exam (Artificial Analysis run) | 6.8% | 11.0% | gpt-oss-20b |
| 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 | 40.5% | 53.2% | gpt-oss-20b |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-20b | Leader |
|---|---|---|---|
| AIME | 42.1% | 86.0% | gpt-oss-20b |
| MATH 500 (Vals AI) | Not measured | 94.2% | Only gpt-oss-20b measured |
| MGSM (Vals AI) | 89.5% | 89.0% | Gemini 2.5 Flash Lite |
| AA Math Index | 53.3 | 89.3 | gpt-oss-20b |
| AIME 2025 (Artificial Analysis run) | 53.3% | 89.3% | gpt-oss-20b |
| 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 index60
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-20b | Leader |
|---|---|---|---|
| MMLU Pro | 79.1% | 71.6% | Gemini 2.5 Flash Lite |
| LegalBench (Vals AI) | 82.0% | 70.8% | Gemini 2.5 Flash Lite |
| CaseLaw (Vals AI) | Not measured | 43.8% | Only gpt-oss-20b measured |
| CorpFin (Vals AI) | 57.6% | 53.1% | Gemini 2.5 Flash Lite |
| TaxEval (Vals AI) | 66.2% | 63.7% | Gemini 2.5 Flash Lite |
| MortgageTax (Vals AI) | 57.6% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedQA (Vals AI) | 88.9% | 82.9% | Gemini 2.5 Flash Lite |
| MedCode (Vals AI) | 34.2% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MMLU Pro (Artificial Analysis run) | 75.9% | 74.8% | Gemini 2.5 Flash Lite |
| 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 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-20b | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 852 | Only gpt-oss-20b measured |
| Design Arena: data viz | Not measured | 933 | Only gpt-oss-20b measured |
| Neither model has a result on the other 7 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-20b | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 30.8% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedScribe (Vals AI) | 75.8% | Not measured | Only Gemini 2.5 Flash Lite measured |
| IFBench | 49.9% | 65.1% | gpt-oss-20b |
| Long context reasoning (AA-LCR) | 55.7% | 34.7% | Gemini 2.5 Flash Lite |
| DTBench | 62.8% | 68.0% | gpt-oss-20b |
| LMCA | 18.1% | 14.5% | Gemini 2.5 Flash Lite |
| 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 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | 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 | Google Gemini 2.5 Flash Lite | OpenAI gpt-oss-20b |
|---|---|---|
| Maker | OpenAI | |
| Weights | No public weights listed | Open weights |
| Released | July 22, 2025 | August 5, 2025 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.10 | $0.03 |
| Output $/Mtok | $0.40 | $0.15 |
| 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 Gemini 2.5 Flash Lite better than gpt-oss-20b for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash Lite for a larger context window (1.05M against 131K tokens) and work measured by LiveCodeBench (Vals AI) or LiveCodeBench (Artificial Analysis run), where it leads.
Which is cheaper, Gemini 2.5 Flash Lite or gpt-oss-20b?
Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 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, Gemini 2.5 Flash Lite or gpt-oss-20b?
Gemini 2.5 Flash Lite, with 1.05M tokens against 131K.
How many benchmarks is the Gemini 2.5 Flash Lite vs gpt-oss-20b comparison based on?
24 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash Lite's coding index rests on 0 independent benchmarks and gpt-oss-20b's on 0. Where only one model has a result, the page says so instead of naming a winner.