Gemini 2.5 Flash Lite vs Ling 3.0 Flash VL
Ling 3.0 Flash VL leads Gemini 2.5 Flash Lite on the Artificial Analysis Intelligence Index, 24.6 to 10.4, and Ling 3.0 Flash VL costs 2.2x less per output token ($0.18 vs $0.40 per million). Updated October 22, 2026; 4 benchmarks have a result for both.
Gemini 2.5 Flash Lite 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 Lite 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 Lite only
- 26
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Ling 3.0 Flash VL
Ling 3.0 Flash VL leads, 24.6 against 10.4.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash VL has a AA Agentic Index result, 28.7.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 2.5 Flash Lite has a GPQA Diamond result, 70.2%.
Directional only
Math
AIME
No call
Only Gemini 2.5 Flash Lite has a AIME result, 42.1%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 2.5 Flash Lite has a MMLU Pro result, 79.1%.
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
Ling 3.0 Flash VL
Gemini 2.5 Flash Lite $0.0003, Ling 3.0 Flash VL $0.0001 per turn.
List prices
At a glance
- Coding index
- Gemini 2.5 Flash Lite not benchmarked, Ling 3.0 Flash VL not benchmarked.
- Widest category
- General, 22.7 points apart on average over 1 shared benchmark.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): Gemini 2.5 Flash Lite 62.5% against Ling 3.0 Flash VL 86.2%, 23.7 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Flash Lite $0.40 against Ling 3.0 Flash VL $0.18 per million output tokens, 2.2x apart.
- Context window
- Gemini 2.5 Flash Lite 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.
| Category | Gemini 2.5 Flash Lite | Bars | Ling 3.0 Flash VL | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 4 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 57.0 | Only Ling 3.0 Flash VL measured |
| LiveCodeBench (Vals AI) | 71.4% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LiveCodeBench (Artificial Analysis run) | 59.3% | Not measured | Only Gemini 2.5 Flash Lite measured |
| SciCode | Not measured | 44.2% | Only Ling 3.0 Flash VL measured |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 38 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash Lite | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.4 | 24.6 | Ling 3.0 Flash VL |
| Epoch Capabilities Index | 133.8 | Not measured | Only Gemini 2.5 Flash Lite measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 28.7 | Only Ling 3.0 Flash VL measured |
| τ²-Bench Telecom | 19.0% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Berkeley Function Calling Leaderboard (BFCL) | 36.9% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Flash Lite | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| GPQA Diamond | 70.2% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MMMU Pro (Vals AI) | 75.4% | Not measured | Only Gemini 2.5 Flash Lite measured |
| GPQA Diamond (Artificial Analysis run) | 62.5% | 86.2% | Ling 3.0 Flash VL |
| Humanity's Last Exam (Artificial Analysis run) | 6.8% | 22.0% | Ling 3.0 Flash VL |
| Kagi LLM Benchmark | 40.5% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AIME | 42.1% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MGSM (Vals AI) | 89.5% | Not measured | Only Gemini 2.5 Flash Lite measured |
| AA Math Index | 53.3 | Not measured | Only Gemini 2.5 Flash Lite measured |
| AIME 2025 (Artificial Analysis run) | 53.3% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| MMLU Pro | 79.1% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LegalBench (Vals AI) | 82.0% | Not measured | Only Gemini 2.5 Flash Lite measured |
| CorpFin (Vals AI) | 57.6% | Not measured | Only Gemini 2.5 Flash Lite measured |
| TaxEval (Vals AI) | 66.2% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MortgageTax (Vals AI) | 57.6% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedQA (Vals AI) | 88.9% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MedCode (Vals AI) | 34.2% | Not measured | Only Gemini 2.5 Flash Lite measured |
| MMLU Pro (Artificial Analysis run) | 75.9% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemini 2.5 Flash Lite | Ling 3.0 Flash VL | 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% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Long context reasoning (AA-LCR) | 55.7% | 78.3% | Ling 3.0 Flash VL |
| DTBench | 62.8% | Not measured | Only Gemini 2.5 Flash Lite measured |
| LMCA | 18.1% | Not measured | Only Gemini 2.5 Flash Lite measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Flash Lite | Ling 3.0 Flash VL | 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
Ling 3.0 Flash VL costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash VL costs less
Agent loop
200K input + 10K output tokens
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.
| Specification | Google Gemini 2.5 Flash Lite | inclusionAI Ling 3.0 Flash VL |
|---|---|---|
| Maker | inclusionAI | |
| Weights | No public weights listed | Open weights |
| Released | July 22, 2025 | September 10, 2026 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.10 | $0.06 |
| Output $/Mtok | $0.40 | $0.18 |
| 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 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 Lite 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 Lite or Ling 3.0 Flash VL?
Gemini 2.5 Flash Lite costs $0.10 per million input tokens and $0.40 per million output tokens; Ling 3.0 Flash VL costs $0.06 and $0.18. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemini 2.5 Flash Lite or Ling 3.0 Flash VL?
Gemini 2.5 Flash Lite, with 1.05M tokens against 131K.
How many benchmarks is the Gemini 2.5 Flash Lite 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 Lite'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.