Ling 3.0 Flash VL vs o1-pro
Ling 3.0 Flash VL leads o1-pro on the Artificial Analysis Intelligence Index, 24.6 to 12.4, and Ling 3.0 Flash VL costs 3333.3x less per output token ($0.18 vs $600.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
Ling 3.0 Flash VL or o1-pro: 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 3333.3x cheaper ($0.18 vs $600.00 per million).
- Shared results
- 1
- Ling 3.0 Flash VL only
- 6
- o1-pro only
- 1
- Like-for-like categories
- 1 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 12.4.
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
Long documents
Listed context window
o1-pro
o1-pro takes 200K 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, o1-pro $0.450 per turn.
List prices
At a glance
- Coding index
- Ling 3.0 Flash VL not benchmarked, o1-pro not benchmarked.
- Widest category
- Intelligence, 12.2 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: Ling 3.0 Flash VL 24.6 against o1-pro 12.4, 12.2 points apart on a 0 to 100 scale.
- Output price
- Ling 3.0 Flash VL $0.18 against o1-pro $600.00 per million output tokens, 3333.3x apart.
- Context window
- Ling 3.0 Flash VL takes 131K tokens, o1-pro 200K.
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 | o1-pro | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards, none shared
| Benchmark | Ling 3.0 Flash VL | o1-pro | Leader |
|---|---|---|---|
| AA Coding Index | 57.0 | Not measured | Only Ling 3.0 Flash VL measured |
| SciCode | 44.2% | Not measured | Only Ling 3.0 Flash VL measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Ling 3.0 Flash VL | o1-pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.6 | 12.4 | Ling 3.0 Flash VL |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Ling 3.0 Flash VL | o1-pro | Leader |
|---|---|---|---|
| AA Agentic Index | 28.7 | Not measured | Only Ling 3.0 Flash VL measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Ling 3.0 Flash VL | o1-pro | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 86.2% | Not measured | Only Ling 3.0 Flash VL measured |
| Humanity's Last Exam (Artificial Analysis run) | 22.0% | Not measured | Only Ling 3.0 Flash VL measured |
| ARC-AGI | Not measured | 23.3% | Only o1-pro measured |
| Neither model has a result on the other 19 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | o1-pro | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | o1-pro | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | o1-pro | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Ling 3.0 Flash VL | o1-pro | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | 78.3% | Not measured | Only Ling 3.0 Flash VL measured |
| Neither model has a result on the other 45 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | o1-pro | 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 | OpenAI o1-pro |
|---|---|---|
| Maker | inclusionAI | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | March 19, 2025 |
| Context window | 131K | 200K |
| Input $/Mtok | $0.06 | $150.00 |
| Output $/Mtok | $0.18 | $600.00 |
| 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 o1-pro 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 3333.3x cheaper ($0.18 vs $600.00 per million).
Which is cheaper, Ling 3.0 Flash VL or o1-pro?
Ling 3.0 Flash VL costs $0.06 per million input tokens and $0.18 per million output tokens; o1-pro costs $150.00 and $600.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Ling 3.0 Flash VL or o1-pro?
o1-pro, with 200K tokens against 131K.
How many benchmarks is the Ling 3.0 Flash VL vs o1-pro comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. Ling 3.0 Flash VL's coding index rests on 0 independent benchmarks and o1-pro's on 0. Where only one model has a result, the page says so instead of naming a winner.