Ling 3.0 Flash VL vs LongCat 2.0
Ling 3.0 Flash VL leads LongCat 2.0 on the Artificial Analysis Intelligence Index, 24.6 to 19.1, and Ling 3.0 Flash VL costs 6.7x less per output token ($0.18 vs $1.20 per million). Updated October 23, 2026; 7 benchmarks have a result for both.
Ling 3.0 Flash VL or LongCat 2.0: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Ling 3.0 Flash VL for output tokens 6.7x cheaper ($0.18 vs $1.20 per million) and work measured by Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 7
- Ling 3.0 Flash VL only
- 0
- LongCat 2.0 only
- 1
- Like-for-like categories
- 5 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 19.1.
Same board, both measured
Agentic work
AA Agentic Index
Ling 3.0 Flash VL
Ling 3.0 Flash VL leads, 28.7 against 14.0.
Same board, both measured
Long documents
Listed context window
LongCat 2.0
LongCat 2.0 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash VL
Ling 3.0 Flash VL $0.0001, LongCat 2.0 $0.0009 per turn.
List prices
At a glance
- Coding index
- Ling 3.0 Flash VL not benchmarked, LongCat 2.0 not benchmarked.
- Widest category
- Agentic work, 14.7 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Agentic Index: Ling 3.0 Flash VL 28.7 against LongCat 2.0 14.0, 14.7 points apart on a 0 to 100 scale.
- Output price
- Ling 3.0 Flash VL $0.18 against LongCat 2.0 $1.20 per million output tokens, 6.7x apart.
- Context window
- Ling 3.0 Flash VL takes 131K tokens, LongCat 2.0 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.
| Category | Ling 3.0 Flash VL | Bars | LongCat 2.0 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 1 | 1 | ||
| General | 1 | 0 | ||
| All shared boards | 6 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Ling 3.0 Flash VL | LongCat 2.0 | Leader |
|---|---|---|---|
| AA Coding Index | 57.0 | 45.3 | Ling 3.0 Flash VL |
| SciCode | 44.2% | 36.3% | Ling 3.0 Flash VL |
| ALE-Bench | Not measured | 793.5 | Only LongCat 2.0 measured |
| Neither model has a result on the other 40 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Ling 3.0 Flash VL | LongCat 2.0 | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.6 | 19.1 | Ling 3.0 Flash VL |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Ling 3.0 Flash VL | LongCat 2.0 | Leader |
|---|---|---|---|
| AA Agentic Index | 28.7 | 14.0 | Ling 3.0 Flash VL |
| Neither model has a result on the other 41 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Ling 3.0 Flash VL | LongCat 2.0 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 86.2% | 78.0% | Ling 3.0 Flash VL |
| Humanity's Last Exam (Artificial Analysis run) | 22.0% | 33.7% | LongCat 2.0 |
| Neither model has a result on the other 21 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | LongCat 2.0 | Leader |
|---|---|---|---|
| Neither model has a result on 14 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | LongCat 2.0 | Leader |
|---|---|---|---|
| Neither model has a result on 20 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | LongCat 2.0 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Ling 3.0 Flash VL | LongCat 2.0 | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | 78.3% | 65.0% | Ling 3.0 Flash VL |
| Neither model has a result on the other 47 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | LongCat 2.0 | 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 | inclusionAI Ling 3.0 Flash VL | Meituan LongCat 2.0 |
|---|---|---|
| Maker | inclusionAI | Meituan |
| Weights | Open weights | Open weights |
| Released | September 10, 2026 | July 20, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.06 | $0.30 |
| Output $/Mtok | $0.18 | $1.20 |
| 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 Ling 3.0 Flash VL better than LongCat 2.0 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Ling 3.0 Flash VL for output tokens 6.7x cheaper ($0.18 vs $1.20 per million) and work measured by Humanity's Last Exam (Artificial Analysis run), where it leads.
Which is cheaper, Ling 3.0 Flash VL or LongCat 2.0?
Ling 3.0 Flash VL costs $0.06 per million input tokens and $0.18 per million output tokens; LongCat 2.0 costs $0.30 and $1.20. Cost per solved task is known for neither of them.
Which has the bigger context window, Ling 3.0 Flash VL or LongCat 2.0?
LongCat 2.0, with 1.05M tokens against 131K.
How many benchmarks is the Ling 3.0 Flash VL vs LongCat 2.0 comparison based on?
7 benchmarks have a result for both models as of October 23, 2026. Ling 3.0 Flash VL's coding index rests on 0 independent benchmarks and LongCat 2.0's on 0. Where only one model has a result, the page says so instead of naming a winner.