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Gemini 2.5 Flash Lite vs GPT-6.1 Sol

GPT-6.1 Sol leads Gemini 2.5 Flash Lite on the Artificial Analysis Intelligence Index, 51.8 to 10.4, and Gemini 2.5 Flash Lite costs 25.0x less per output token ($0.40 vs $10.00 per million). Updated October 21, 2026; 9 benchmarks have a result for both.

Gemini 2.5 Flash LiteGoogle
Coding
No data
Overall
No data
Output $/M
$0.40
0
GPT-6.1 SolOpenAI
Coding
82.4
Overall
81.4
Output $/M
$10.00
9
vs boards won of 9 shared

Gemini 2.5 Flash Lite or GPT-6.1 Sol: which to pick

Only GPT-6.1 Sol has a coding score, 82.4 on the Vibe Coding Index; Gemini 2.5 Flash Lite has none, so the two cannot be ranked on coding.

Pick Gemini 2.5 Flash Lite for output tokens 25.0x cheaper ($0.40 vs $10.00 per million).

Shared results
9
Gemini 2.5 Flash Lite only
21
GPT-6.1 Sol only
89
Like-for-like categories
4 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.

At a glance

Coding index
Gemini 2.5 Flash Lite not benchmarked, GPT-6.1 Sol 82.4 from 5 benchmarks.
Widest category
Reasoning, 46.1 points apart on average over 1 shared benchmark.
Widest single gap
Humanity's Last Exam (Artificial Analysis run): Gemini 2.5 Flash Lite 6.8% against GPT-6.1 Sol 52.9%, 46.1 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Flash Lite $0.40 against GPT-6.1 Sol $10.00 per million output tokens, 25.0x apart.
Context window
Gemini 2.5 Flash Lite takes 1.05M tokens, GPT-6.1 Sol 1.05M.

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.

Boards won, where both have a result
CategoryGemini 2.5 Flash LiteBarsGPT-6.1 SolTies
Intelligence02
Reasoning01
Knowledge01
General05
All shared boards09
CodingDirectional onlySix of these boards feed the Vibe Coding Index21 boards, none shared
Coding benchmarks for Gemini 2.5 Flash Lite and GPT-6.1 Sol
BenchmarkGemini 2.5 Flash LiteGPT-6.1 SolLeader
LiveBench codingNot measured96.0%Only GPT-6.1 Sol measured
LMArena WebDevNot measured1753Only GPT-6.1 Sol measured
LiveCodeBench (Vals AI)71.4%Not measuredOnly Gemini 2.5 Flash Lite measured
Terminal-Bench 4 (Vals AI)Not measured55.0%Only GPT-6.1 Sol measured
Vibe Code Bench (Vals AI)Not measured88.9%Only GPT-6.1 Sol measured
Code migration (Vals AI)Not measured65.1%Only GPT-6.1 Sol measured
ProgramBench (Vals AI)Not measured3.0%Only GPT-6.1 Sol measured
IOI (Vals AI)Not measured96.9%Only GPT-6.1 Sol measured
SWE-bench Multimodal (Vals AI)Not measured43.5%Only GPT-6.1 Sol measured
CyberBench (Vals AI)Not measured39.3%Only GPT-6.1 Sol measured
LiveCodeBench (Artificial Analysis run)59.3%Not measuredOnly Gemini 2.5 Flash Lite measured
SciCodeNot measured55.8%Only GPT-6.1 Sol measured
Terminal-Bench Hard (Artificial Analysis run)4.5%Not measuredOnly Gemini 2.5 Flash Lite measured
FrontierCodeNot measured50.2%Only GPT-6.1 Sol measured
ALE-BenchNot measured2743.8Only GPT-6.1 Sol measured
LMArena Text: codingNot measured1478Only GPT-6.1 Sol measured
LMArena Text: software and ITNot measured1476Only GPT-6.1 Sol measured
LMArena WebDev: ReactNot measured1754Only GPT-6.1 Sol measured
LMArena WebDev: HTMLNot measured1800Only GPT-6.1 Sol measured
LMArena WebDev: from an imageNot measured1702Only GPT-6.1 Sol measured
SciCodeNot measured9.2%Only GPT-6.1 Sol measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemini 2.5 Flash Lite and GPT-6.1 Sol
BenchmarkGemini 2.5 Flash LiteGPT-6.1 SolLeader
AA Intelligence Index10.451.8GPT-6.1 Sol
Epoch Capabilities Index133.8168.4GPT-6.1 Sol
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
Agentic work benchmarks for Gemini 2.5 Flash Lite and GPT-6.1 Sol
BenchmarkGemini 2.5 Flash LiteGPT-6.1 SolLeader
Design Arena: agents building web appsNot measured1306Only GPT-6.1 Sol measured
Design Arena: agents building mobile appsNot measured1204Only GPT-6.1 Sol measured
Design Arena: spreadsheetsNot measured1242Only GPT-6.1 Sol measured
LiveBench researchNot measured83.5%Only GPT-6.1 Sol measured
LiveBench browserNot measured88.0%Only GPT-6.1 Sol measured
LiveBench long agenticNot measured73.0%Only GPT-6.1 Sol measured
SREBench (Vals AI)Not measured50.8%Only GPT-6.1 Sol measured
Finance Agent (Vals AI)Not measured52.0%Only GPT-6.1 Sol measured
Tax Agent Bench (Vals AI)Not measured21.8%Only GPT-6.1 Sol measured
Legal Research Bench (Vals AI)Not measured38.5%Only GPT-6.1 Sol measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured6.3%Only GPT-6.1 Sol measured
Excel Modeling Benchmark (Vals AI)Not measured70.8%Only GPT-6.1 Sol measured
BioMysteryBench (Vals AI)Not measured79.6%Only GPT-6.1 Sol measured
Terminal-Bench-Science (Vals AI)Not measured52.9%Only GPT-6.1 Sol measured
Vals Science IndexNot measured59.6%Only GPT-6.1 Sol measured
Robo-bench (Vals AI)Not measured28.3%Only GPT-6.1 Sol measured
τ²-Bench Telecom19.0%Not measuredOnly Gemini 2.5 Flash Lite measured
APEX-AgentsNot measured60.0%Only GPT-6.1 Sol measured
SpireClimbNot measured24.7%Only GPT-6.1 Sol measured
Berkeley Function Calling Leaderboard (BFCL)36.9%Not measuredOnly Gemini 2.5 Flash Lite measured
Neither model has a result on the other 21 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for Gemini 2.5 Flash Lite and GPT-6.1 Sol
BenchmarkGemini 2.5 Flash LiteGPT-6.1 SolLeader
GPQA Diamond70.2%Not measuredOnly Gemini 2.5 Flash Lite measured
LiveBench reasoningNot measured92.6%Only GPT-6.1 Sol measured
MysteryMechanism (Vals AI)Not measured46.4%Only GPT-6.1 Sol measured
MMMU Pro (Vals AI)75.4%Not measuredOnly Gemini 2.5 Flash Lite measured
GPQA Diamond (Artificial Analysis run)62.5%Not measuredOnly Gemini 2.5 Flash Lite measured
Humanity's Last Exam (Artificial Analysis run)6.8%52.9%GPT-6.1 Sol
GPQA Diamond (Epoch AI run)Not measured95.4%Only GPT-6.1 Sol measured
ARC-AGINot measured98.5%Only GPT-6.1 Sol measured
ARC-AGI-2Not measured94.2%Only GPT-6.1 Sol measured
Chess puzzlesNot measured68.0%Only GPT-6.1 Sol measured
Mystery game puzzlesNot measured80.0%Only GPT-6.1 Sol measured
EBR-benchNot measured54.3%Only GPT-6.1 Sol measured
LMArena Text: hard promptsNot measured1463Only GPT-6.1 Sol measured
LMArena Text: expertNot measured1489Only GPT-6.1 Sol measured
LMArena Text: hard prompts in EnglishNot measured1465Only GPT-6.1 Sol measured
LMArena Vision: diagramsNot measured1306Only GPT-6.1 Sol measured
LMArena Vision: homeworkNot measured1356Only GPT-6.1 Sol measured
Kagi LLM Benchmark40.5%Not measuredOnly Gemini 2.5 Flash Lite measured
Neither model has a result on the other 4 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Math benchmarks for Gemini 2.5 Flash Lite and GPT-6.1 Sol
BenchmarkGemini 2.5 Flash LiteGPT-6.1 SolLeader
AIME42.1%Not measuredOnly Gemini 2.5 Flash Lite measured
MGSM (Vals AI)89.5%Not measuredOnly Gemini 2.5 Flash Lite measured
AA Math Index53.3Not measuredOnly Gemini 2.5 Flash Lite measured
AIME 2025 (Artificial Analysis run)53.3%Not measuredOnly Gemini 2.5 Flash Lite measured
OTIS Mock AIMENot measured100.0%Only GPT-6.1 Sol measured
FrontierMath, tiers 1 to 3Not measured93.7%Only GPT-6.1 Sol measured
FrontierMath, tier 4Not measured100.0%Only GPT-6.1 Sol measured
ProofBenchNot measured99.0%Only GPT-6.1 Sol measured
LMArena Text: mathNot measured1489Only GPT-6.1 Sol measured
LMArena Text: mathematical workNot measured1513Only GPT-6.1 Sol measured
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
Knowledge benchmarks for Gemini 2.5 Flash Lite and GPT-6.1 Sol
BenchmarkGemini 2.5 Flash LiteGPT-6.1 SolLeader
MMLU Pro79.1%Not measuredOnly Gemini 2.5 Flash Lite measured
LegalBench (Vals AI)82.0%Not measuredOnly Gemini 2.5 Flash Lite measured
CorpFin (Vals AI)57.6%Not measuredOnly Gemini 2.5 Flash Lite measured
TaxEval (Vals AI)66.2%Not measuredOnly Gemini 2.5 Flash Lite measured
MortgageTax (Vals AI)57.6%Not measuredOnly Gemini 2.5 Flash Lite measured
MedQA (Vals AI)88.9%Not measuredOnly Gemini 2.5 Flash Lite measured
MedCode (Vals AI)34.2%48.8%GPT-6.1 Sol
MMLU Pro (Artificial Analysis run)75.9%Not measuredOnly Gemini 2.5 Flash Lite measured
SimpleQA VerifiedNot measured73.9%Only GPT-6.1 Sol measured
LMArena Text: scienceNot measured1444Only GPT-6.1 Sol measured
LMArena Text: medicine and healthcareNot measured1433Only GPT-6.1 Sol measured
LMArena Text: legal and governmentNot measured1471Only GPT-6.1 Sol measured
LMArena Text: business and financeNot measured1445Only GPT-6.1 Sol measured
FACTS Benchmark SuiteNot measured75.3%Only GPT-6.1 Sol measured
Neither model has a result on the other 4 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Gemini 2.5 Flash Lite and GPT-6.1 Sol
BenchmarkGemini 2.5 Flash LiteGPT-6.1 SolLeader
Design Arena: websitesNot measured1321Only GPT-6.1 Sol measured
Design Arena: UI componentsNot measured1330Only GPT-6.1 Sol measured
Design Arena: game devNot measured1389Only GPT-6.1 Sol measured
Design Arena: data vizNot measured1280Only GPT-6.1 Sol measured
Design Arena: 3DNot measured1463Only GPT-6.1 Sol measured
Design Arena: all code categoriesNot measured1346Only GPT-6.1 Sol measured
LiveBench designNot measured82.1%Only GPT-6.1 Sol measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index05
General benchmarks for Gemini 2.5 Flash Lite and GPT-6.1 Sol
BenchmarkGemini 2.5 Flash LiteGPT-6.1 SolLeader
Vals IndexNot measured63.9%Only GPT-6.1 Sol measured
LiveBench data analysisNot measured82.7%Only GPT-6.1 Sol measured
Public Benefits Bench (Vals AI)Not measured59.3%Only GPT-6.1 Sol measured
SAGE (Vals AI)30.8%46.5%GPT-6.1 Sol
MedScribe (Vals AI)75.8%86.5%GPT-6.1 Sol
IFBench49.9%Not measuredOnly Gemini 2.5 Flash Lite measured
Long context reasoning (AA-LCR)55.7%84.0%GPT-6.1 Sol
DTBench62.8%96.5%GPT-6.1 Sol
LMCA18.1%62.8%GPT-6.1 Sol
Furniture assemblyNot measured80.0%Only GPT-6.1 Sol measured
LMArena TextNot measured1443Only GPT-6.1 Sol measured
LMArena Text: instruction followingNot measured1466Only GPT-6.1 Sol measured
LMArena Text: creative writingNot measured1425Only GPT-6.1 Sol measured
LMArena VisionNot measured1288Only GPT-6.1 Sol measured
LMArena Text: EnglishNot measured1450Only GPT-6.1 Sol measured
LMArena Text: non-EnglishNot measured1433Only GPT-6.1 Sol measured
LMArena Text: ChineseNot measured1487Only GPT-6.1 Sol measured
LMArena Text: FrenchNot measured1460Only GPT-6.1 Sol measured
LMArena Text: SpanishNot measured1439Only GPT-6.1 Sol measured
LMArena Text: RussianNot measured1457Only GPT-6.1 Sol measured
LMArena Text: multi-turnNot measured1442Only GPT-6.1 Sol measured
LMArena Text: longer queriesNot measured1458Only GPT-6.1 Sol measured
LMArena Text: writing and languageNot measured1444Only GPT-6.1 Sol measured
LMArena Text: entertainment and mediaNot measured1426Only GPT-6.1 Sol measured
LMArena Vision: EnglishNot measured1274Only GPT-6.1 Sol measured
LMArena Vision: reading textNot measured1289Only GPT-6.1 Sol measured
LMArena Vision: creative writingNot measured1301Only GPT-6.1 Sol measured
Neither model has a result on the other 19 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Flash Lite and GPT-6.1 Sol
BenchmarkGemini 2.5 Flash LiteGPT-6.1 SolLeader
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$0.0003Fits in one request
GPT-6.1 Sol$0.0070Fits in one request

Gemini 2.5 Flash Lite costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Flash Lite$0.0062Fits in one request
GPT-6.1 Sol$0.130Fits in one request

Gemini 2.5 Flash Lite costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Flash Lite$0.024Fits in one request
GPT-6.1 Sol$0.500Fits in one request

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.

Specifications of Gemini 2.5 Flash Lite and GPT-6.1 Sol
SpecificationGoogle Gemini 2.5 Flash LiteOpenAI GPT-6.1 Sol
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedJuly 22, 2025September 29, 2026
Context window1.05M1.05M
Input $/Mtok$0.10$2.00
Output $/Mtok$0.40$10.00
Coding indexNot benchmarked82.4
Independent measurements behind it05
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Flash Lite better than GPT-6.1 Sol for coding?

Only GPT-6.1 Sol has a coding score, 82.4 on the Vibe Coding Index; Gemini 2.5 Flash Lite has none, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash Lite for output tokens 25.0x cheaper ($0.40 vs $10.00 per million).

Which is cheaper, Gemini 2.5 Flash Lite or GPT-6.1 Sol?

Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; GPT-6.1 Sol costs $2.00 and $10.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemini 2.5 Flash Lite or GPT-6.1 Sol?

GPT-6.1 Sol, with 1.05M tokens against 1.05M.

How many benchmarks is the Gemini 2.5 Flash Lite vs GPT-6.1 Sol comparison based on?

9 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-6.1 Sol's on 5. Where only one model has a result, the page says so instead of naming a winner.

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