Gemini 2.5 Flash Lite vs gpt-oss-120b
gpt-oss-120b leads Gemini 2.5 Flash Lite on the Artificial Analysis Intelligence Index, 11.6 to 10.4, and Gemini 2.5 Flash Lite costs 1.3x less per output token ($0.40 vs $0.50 per million). Updated October 21, 2026; 24 benchmarks have a result for both.
Gemini 2.5 Flash Lite or gpt-oss-120b: 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 output tokens 1.3x cheaper ($0.40 vs $0.50 per million) and a larger context window (1.05M against 131K tokens).
- Shared results
- 24
- Gemini 2.5 Flash Lite only
- 6
- gpt-oss-120b only
- 57
- 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
gpt-oss-120b
gpt-oss-120b leads, 11.6 against 10.4.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only gpt-oss-120b has a AA Agentic Index result, 3.7.
Directional only
Reasoning
GPQA Diamond
gpt-oss-120b
gpt-oss-120b leads, 78.5% against 70.2%.
Same board, both measured
Math
AIME
gpt-oss-120b
gpt-oss-120b leads, 92.6% against 42.1%.
Same board, both measured
Knowledge
MMLU Pro
gpt-oss-120b
gpt-oss-120b leads, 79.2% against 79.1%.
Same board, both measured
Web design
Design Arena: websites
No call
Only gpt-oss-120b has a Design Arena: websites result, 968.
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
Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite $0.0003, gpt-oss-120b $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only gpt-oss-120b has the number, $0.51.
Directional only
At a glance
- Coding index
- Gemini 2.5 Flash Lite not benchmarked, gpt-oss-120b not benchmarked.
- Widest category
- Agentic work, 46.8 points apart on average over 1 shared benchmark.
- Widest single gap
- AIME: Gemini 2.5 Flash Lite 42.1% against gpt-oss-120b 92.6%, 50.5 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash Lite $0.40 against gpt-oss-120b $0.50 per million output tokens, 1.3x apart.
- Context window
- Gemini 2.5 Flash Lite takes 1.05M tokens, gpt-oss-120b 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-120b | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 4 | ||
| Math | 0 | 4 | ||
| Knowledge | 1 | 5 | ||
| General | 1 | 3 | ||
| All shared boards | 2 | 22 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-120b | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 41.8% | Only gpt-oss-120b measured |
| SWE-bench Verified | Not measured | 26.0% | Only gpt-oss-120b measured |
| AA Coding Index | Not measured | 30.4 | Only gpt-oss-120b measured |
| LiveCodeBench (Vals AI) | 71.4% | 83.2% | gpt-oss-120b |
| SWE-bench Verified (Vals AI) | Not measured | 33.6% | Only gpt-oss-120b measured |
| LiveCodeBench (Artificial Analysis run) | 59.3% | 87.8% | gpt-oss-120b |
| SciCode | Not measured | 34.0% | Only gpt-oss-120b measured |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | 23.5% | gpt-oss-120b |
| Terminal-Bench | Not measured | 18.7% | Only gpt-oss-120b measured |
| WeirdML | Not measured | 48.2% | Only gpt-oss-120b measured |
| ALE-Bench | Not measured | 575.6 | Only gpt-oss-120b measured |
| LMArena Text: coding | Not measured | 1379 | Only gpt-oss-120b measured |
| LMArena Text: software and IT | Not measured | 1387 | Only gpt-oss-120b measured |
| SciCode | Not measured | 7.7% | Only gpt-oss-120b measured |
| Neither model has a result on the other 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.4 | 11.6 | gpt-oss-120b |
| Epoch Capabilities Index | 133.8 | 139.8 | gpt-oss-120b |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-120b | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 3.7 | Only gpt-oss-120b measured |
| τ²-Bench Telecom | 19.0% | 65.8% | gpt-oss-120b |
| APEX-Agents | Not measured | 4.4% | Only gpt-oss-120b measured |
| METR time horizons | Not measured | 56.6% | Only gpt-oss-120b measured |
| Vending-Bench 2 | Not measured | -$22 | Only gpt-oss-120b measured |
| Berkeley Function Calling Leaderboard (BFCL) | 36.9% | Not measured | Only Gemini 2.5 Flash Lite measured |
| BrowseComp-Plus | Not measured | 67.0% | Only gpt-oss-120b measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-120b | Leader |
|---|---|---|---|
| GPQA Diamond | 70.2% | 78.5% | gpt-oss-120b |
| MMMU Pro (Vals AI) | 75.4% | Not measured | Only Gemini 2.5 Flash Lite measured |
| GPQA Diamond (Artificial Analysis run) | 62.5% | 78.2% | gpt-oss-120b |
| Humanity's Last Exam (Artificial Analysis run) | 6.8% | 19.6% | gpt-oss-120b |
| GPQA Diamond (Epoch AI run) | Not measured | 75.8% | Only gpt-oss-120b measured |
| SimpleBench | Not measured | 22.1% | Only gpt-oss-120b measured |
| Mystery game puzzles | Not measured | 2.0% | Only gpt-oss-120b measured |
| LMArena Text: hard prompts | Not measured | 1364 | Only gpt-oss-120b measured |
| LMArena Text: expert | Not measured | 1356 | Only gpt-oss-120b measured |
| LMArena Text: hard prompts in English | Not measured | 1368 | Only gpt-oss-120b measured |
| Kagi LLM Benchmark | 40.5% | 58.6% | gpt-oss-120b |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-120b | Leader |
|---|---|---|---|
| AIME | 42.1% | 92.6% | gpt-oss-120b |
| MATH 500 (Vals AI) | Not measured | 94.8% | Only gpt-oss-120b measured |
| MGSM (Vals AI) | 89.5% | 92.0% | gpt-oss-120b |
| AA Math Index | 53.3 | 93.4 | gpt-oss-120b |
| AIME 2025 (Artificial Analysis run) | 53.3% | 93.4% | gpt-oss-120b |
| OTIS Mock AIME | Not measured | 88.9% | Only gpt-oss-120b measured |
| LMArena Text: math | Not measured | 1389 | Only gpt-oss-120b measured |
| LMArena Text: mathematical work | Not measured | 1386 | Only gpt-oss-120b measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-120b | Leader |
|---|---|---|---|
| MMLU Pro | 79.1% | 79.2% | gpt-oss-120b |
| LegalBench (Vals AI) | 82.0% | 75.9% | Gemini 2.5 Flash Lite |
| CaseLaw (Vals AI) | Not measured | 48.8% | Only gpt-oss-120b measured |
| CorpFin (Vals AI) | 57.6% | 58.2% | gpt-oss-120b |
| TaxEval (Vals AI) | 66.2% | 71.6% | gpt-oss-120b |
| MortgageTax (Vals AI) | 57.6% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedQA (Vals AI) | 88.9% | 91.4% | gpt-oss-120b |
| MedCode (Vals AI) | 34.2% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MMLU Pro (Artificial Analysis run) | 75.9% | 80.8% | gpt-oss-120b |
| LMArena Text: science | Not measured | 1382 | Only gpt-oss-120b measured |
| LMArena Text: medicine and healthcare | Not measured | 1388 | Only gpt-oss-120b measured |
| LMArena Text: legal and government | Not measured | 1355 | Only gpt-oss-120b measured |
| LMArena Text: business and finance | Not measured | 1359 | Only gpt-oss-120b measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-120b | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 968 | Only gpt-oss-120b measured |
| Design Arena: UI components | Not measured | 927 | Only gpt-oss-120b measured |
| Design Arena: game dev | Not measured | 992 | Only gpt-oss-120b measured |
| Design Arena: data viz | Not measured | 987 | Only gpt-oss-120b measured |
| Design Arena: 3D | Not measured | 901 | Only gpt-oss-120b measured |
| Design Arena: all code categories | Not measured | 963 | Only gpt-oss-120b measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Gemini 2.5 Flash Lite | gpt-oss-120b | 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% | 69.0% | gpt-oss-120b |
| Long context reasoning (AA-LCR) | 55.7% | 52.0% | Gemini 2.5 Flash Lite |
| DTBench | 62.8% | 76.3% | gpt-oss-120b |
| LMCA | 18.1% | 22.1% | gpt-oss-120b |
| Fiction.LiveBench | Not measured | 44.4% | Only gpt-oss-120b measured |
| Creative writing (Lech Mazur) | Not measured | 77.1% | Only gpt-oss-120b measured |
| Surface Evolver Bench | Not measured | 25.0% | Only gpt-oss-120b measured |
| LMArena Text | Not measured | 1366 | Only gpt-oss-120b measured |
| LMArena Text: instruction following | Not measured | 1318 | Only gpt-oss-120b measured |
| LMArena Text: creative writing | Not measured | 1274 | Only gpt-oss-120b measured |
| LMArena Text: English | Not measured | 1375 | Only gpt-oss-120b measured |
| LMArena Text: non-English | Not measured | 1351 | Only gpt-oss-120b measured |
| LMArena Text: Chinese | Not measured | 1385 | Only gpt-oss-120b measured |
| LMArena Text: German | Not measured | 1353 | Only gpt-oss-120b measured |
| LMArena Text: Japanese | Not measured | 1331 | Only gpt-oss-120b measured |
| LMArena Text: Korean | Not measured | 1282 | Only gpt-oss-120b measured |
| LMArena Text: French | Not measured | 1370 | Only gpt-oss-120b measured |
| LMArena Text: Spanish | Not measured | 1389 | Only gpt-oss-120b measured |
| LMArena Text: Russian | Not measured | 1343 | Only gpt-oss-120b measured |
| LMArena Text: Polish | Not measured | 1353 | Only gpt-oss-120b measured |
| LMArena Text: multi-turn | Not measured | 1340 | Only gpt-oss-120b measured |
| LMArena Text: longer queries | Not measured | 1319 | Only gpt-oss-120b measured |
| LMArena Text: writing and language | Not measured | 1306 | Only gpt-oss-120b measured |
| LMArena Text: entertainment and media | Not measured | 1292 | Only gpt-oss-120b measured |
| Neither model has a result on the other 20 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-120b | 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
Gemini 2.5 Flash Lite costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Flash Lite costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Flash Lite 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-120b |
|---|---|---|
| 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 | $0.10 |
| Output $/Mtok | $0.40 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | $0.51 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Flash Lite better than gpt-oss-120b for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash Lite for output tokens 1.3x cheaper ($0.40 vs $0.50 per million) and a larger context window (1.05M against 131K tokens).
Which is cheaper, Gemini 2.5 Flash Lite or gpt-oss-120b?
Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; gpt-oss-120b costs $0.10 and $0.50. Cost per solved task is known for gpt-oss-120b only.
Which has the bigger context window, Gemini 2.5 Flash Lite or gpt-oss-120b?
Gemini 2.5 Flash Lite, with 1.05M tokens against 131K.
How many benchmarks is the Gemini 2.5 Flash Lite vs gpt-oss-120b 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-120b's on 1. Where only one model has a result, the page says so instead of naming a winner.