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Gemini 2.5 Flash vs Ling 3.0 Flash VL

Ling 3.0 Flash VL leads Gemini 2.5 Flash on the Artificial Analysis Intelligence Index, 24.6 to 15.5, and Ling 3.0 Flash VL costs 13.9x less per output token ($0.18 vs $2.50 per million). Updated October 22, 2026; 4 benchmarks have a result for both.

Gemini 2.5 FlashGoogle
Coding
No data
Overall
34.3
Output $/M
$2.50
0
Ling 3.0 Flash VLinclusionAI
Coding
No data
Overall
No data
Output $/M
$0.18
4
vs boards won of 4 shared

Gemini 2.5 Flash or Ling 3.0 Flash VL: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Gemini 2.5 Flash for a larger context window (1.05M against 131K tokens) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.

Shared results
4
Gemini 2.5 Flash only
69
Ling 3.0 Flash VL only
3
Like-for-like categories
3 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 not benchmarked, Ling 3.0 Flash VL not benchmarked.
Widest category
General, 13.0 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): Gemini 2.5 Flash 65.3% against Ling 3.0 Flash VL 78.3%, 13.0 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Flash $2.50 against Ling 3.0 Flash VL $0.18 per million output tokens, 13.9x apart.
Context window
Gemini 2.5 Flash takes 1.05M tokens, Ling 3.0 Flash VL 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.

Boards won, where both have a result
CategoryGemini 2.5 FlashBarsLing 3.0 Flash VLTies
Intelligence01
Reasoning02
General01
All shared boards04
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
Coding benchmarks for Gemini 2.5 Flash and Ling 3.0 Flash VL
BenchmarkGemini 2.5 FlashLing 3.0 Flash VLLeader
SWE-bench Verified28.7%Not measuredOnly Gemini 2.5 Flash measured
AA Coding IndexNot measured57.0Only Ling 3.0 Flash VL measured
LiveCodeBench (Artificial Analysis run)69.5%Not measuredOnly Gemini 2.5 Flash measured
SciCodeNot measured44.2%Only Ling 3.0 Flash VL measured
Terminal-Bench Hard (Artificial Analysis run)13.6%Not measuredOnly Gemini 2.5 Flash measured
Terminal-Bench17.1%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: coding1423Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: software and IT1425Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Gemini 2.5 Flash and Ling 3.0 Flash VL
BenchmarkGemini 2.5 FlashLing 3.0 Flash VLLeader
AA Intelligence Index15.524.6Ling 3.0 Flash VL
Epoch Capabilities Index142.9Not measuredOnly Gemini 2.5 Flash measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Agentic work benchmarks for Gemini 2.5 Flash and Ling 3.0 Flash VL
BenchmarkGemini 2.5 FlashLing 3.0 Flash VLLeader
AA Agentic IndexNot measured28.7Only Ling 3.0 Flash VL measured
τ²-Bench Telecom31.6%Not measuredOnly Gemini 2.5 Flash measured
BALROG33.5%Not measuredOnly Gemini 2.5 Flash measured
Vending-Bench 2$549Not measuredOnly Gemini 2.5 Flash measured
Berkeley Function Calling Leaderboard (BFCL)56.2%Not measuredOnly Gemini 2.5 Flash measured
BrowseComp-Plus39.9%Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for Gemini 2.5 Flash and Ling 3.0 Flash VL
BenchmarkGemini 2.5 FlashLing 3.0 Flash VLLeader
GPQA Diamond (Artificial Analysis run)79.0%86.2%Ling 3.0 Flash VL
Humanity's Last Exam (Artificial Analysis run)12.1%22.0%Ling 3.0 Flash VL
ARC-AGI33.3%Not measuredOnly Gemini 2.5 Flash measured
ARC-AGI-22.5%Not measuredOnly Gemini 2.5 Flash measured
SimpleBench41.2%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: hard prompts1422Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: expert1426Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: hard prompts in English1420Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: diagrams1245Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: homework1244Not measuredOnly Gemini 2.5 Flash measured
Kagi LLM Benchmark56.8%Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 11 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Gemini 2.5 Flash and Ling 3.0 Flash VL
BenchmarkGemini 2.5 FlashLing 3.0 Flash VLLeader
AA Math Index73.3Not measuredOnly Gemini 2.5 Flash measured
AIME 2025 (Artificial Analysis run)73.3%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: math1411Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: mathematical work1422Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Knowledge benchmarks for Gemini 2.5 Flash and Ling 3.0 Flash VL
BenchmarkGemini 2.5 FlashLing 3.0 Flash VLLeader
MedCode (Vals AI)40.4%Not measuredOnly Gemini 2.5 Flash measured
MMLU Pro (Artificial Analysis run)83.2%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: science1433Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: medicine and healthcare1428Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: legal and government1430Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: business and finance1404Not measuredOnly Gemini 2.5 Flash measured
FACTS Benchmark Suite47.2%Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 11 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 and Ling 3.0 Flash VL
BenchmarkGemini 2.5 FlashLing 3.0 Flash VLLeader
Design Arena: websites1074Not measuredOnly Gemini 2.5 Flash measured
Design Arena: UI components1003Not measuredOnly Gemini 2.5 Flash measured
Design Arena: game dev1004Not measuredOnly Gemini 2.5 Flash measured
Design Arena: data viz1060Not measuredOnly Gemini 2.5 Flash measured
Design Arena: 3D1020Not measuredOnly Gemini 2.5 Flash measured
Design Arena: all code categories1058Not measuredOnly Gemini 2.5 Flash measured
Design Arena: SVG1020Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
General benchmarks for Gemini 2.5 Flash and Ling 3.0 Flash VL
BenchmarkGemini 2.5 FlashLing 3.0 Flash VLLeader
SAGE (Vals AI)44.8%Not measuredOnly Gemini 2.5 Flash measured
MedScribe (Vals AI)83.0%Not measuredOnly Gemini 2.5 Flash measured
IFBench50.3%Not measuredOnly Gemini 2.5 Flash measured
Long context reasoning (AA-LCR)65.3%78.3%Ling 3.0 Flash VL
DTBench76.5%Not measuredOnly Gemini 2.5 Flash measured
LMCA27.5%Not measuredOnly Gemini 2.5 Flash measured
LMArena Text1417Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: instruction following1405Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: creative writing1400Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision1235Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: English1418Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: non-English1409Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Chinese1449Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: German1417Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Japanese1396Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Korean1385Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: French1432Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Spanish1422Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Russian1415Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Polish1413Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: multi-turn1408Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: longer queries1419Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: writing and language1405Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: entertainment and media1393Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: English1239Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: Chinese1284Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: reading text1237Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: humor1225Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: captioning1277Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: recognizing things1252Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: creative writing1241Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 15 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 and Ling 3.0 Flash VL
BenchmarkGemini 2.5 FlashLing 3.0 Flash VLLeader
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$0.0015Fits in one request
Ling 3.0 Flash VL$0.0001Fits in one request

Ling 3.0 Flash VL costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Flash$0.022Fits in one request
Ling 3.0 Flash VL$0.0035Fits in one request

Ling 3.0 Flash VL costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Flash$0.085Fits in one request
Ling 3.0 Flash VL$0.014Exceeds the context window

Ling 3.0 Flash VL 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 and Ling 3.0 Flash VL
SpecificationGoogle Gemini 2.5 FlashinclusionAI Ling 3.0 Flash VL
MakerGoogleinclusionAI
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025September 10, 2026
Context window1.05M131K
Input $/Mtok$0.30$0.06
Output $/Mtok$2.50$0.18
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved task$0.466Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Flash better than Ling 3.0 Flash VL for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash for a larger context window (1.05M against 131K tokens) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, Gemini 2.5 Flash or Ling 3.0 Flash VL?

Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; Ling 3.0 Flash VL costs $0.06 and $0.18. Cost per solved task is known for Gemini 2.5 Flash only.

Which has the bigger context window, Gemini 2.5 Flash or Ling 3.0 Flash VL?

Gemini 2.5 Flash, with 1.05M tokens against 131K.

How many benchmarks is the Gemini 2.5 Flash vs Ling 3.0 Flash VL comparison based on?

4 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Flash's coding index rests on 0 independent benchmarks and Ling 3.0 Flash VL's on 0. Where only one model has a result, the page says so instead of naming a winner.

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