Ling 3.0 Flash VL vs Step 3.5 Flash
Ling 3.0 Flash VL leads Step 3.5 Flash on the Artificial Analysis Intelligence Index, 24.6 to 17.0, and Ling 3.0 Flash VL costs 1.7x less per output token ($0.18 vs $0.30 per million). Updated October 22, 2026; 4 benchmarks have a result for both.
Ling 3.0 Flash VL or Step 3.5 Flash: 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 1.7x cheaper ($0.18 vs $0.30 per million) and work measured by Humanity's Last Exam (Artificial Analysis run), where it leads.
- Shared results
- 4
- Ling 3.0 Flash VL only
- 3
- Step 3.5 Flash only
- 31
- 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 17.0.
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
Step 3.5 Flash
Step 3.5 Flash takes 262K 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, Step 3.5 Flash $0.0003 per turn.
List prices
At a glance
- Coding index
- Ling 3.0 Flash VL not benchmarked, Step 3.5 Flash not benchmarked.
- Widest category
- General, 15.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Ling 3.0 Flash VL 78.3% against Step 3.5 Flash 63.0%, 15.3 points apart on a 0 to 100 scale.
- Output price
- Ling 3.0 Flash VL $0.18 against Step 3.5 Flash $0.30 per million output tokens, 1.7x apart.
- Context window
- Ling 3.0 Flash VL takes 131K tokens, Step 3.5 Flash 262K.
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 | Step 3.5 Flash | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 1 | ||
| General | 1 | 0 | ||
| All shared boards | 3 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards, none shared
| Benchmark | Ling 3.0 Flash VL | Step 3.5 Flash | 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 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 32.6% | Only Step 3.5 Flash measured |
| LMArena Text: coding | Not measured | 1436 | Only Step 3.5 Flash measured |
| LMArena Text: software and IT | Not measured | 1434 | Only Step 3.5 Flash measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Ling 3.0 Flash VL | Step 3.5 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.6 | 17.0 | 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 index2 boards, none shared
| Benchmark | Ling 3.0 Flash VL | Step 3.5 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 28.7 | Not measured | Only Ling 3.0 Flash VL measured |
| τ²-Bench Telecom | Not measured | 94.4% | Only Step 3.5 Flash measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Ling 3.0 Flash VL | Step 3.5 Flash | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 86.2% | 83.1% | Ling 3.0 Flash VL |
| Humanity's Last Exam (Artificial Analysis run) | 22.0% | 24.5% | Step 3.5 Flash |
| LMArena Text: hard prompts | Not measured | 1411 | Only Step 3.5 Flash measured |
| LMArena Text: expert | Not measured | 1421 | Only Step 3.5 Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1421 | Only Step 3.5 Flash measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Ling 3.0 Flash VL | Step 3.5 Flash | Leader |
|---|---|---|---|
| LMArena Text: math | Not measured | 1408 | Only Step 3.5 Flash measured |
| LMArena Text: mathematical work | Not measured | 1421 | Only Step 3.5 Flash measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Ling 3.0 Flash VL | Step 3.5 Flash | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1415 | Only Step 3.5 Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1408 | Only Step 3.5 Flash measured |
| LMArena Text: legal and government | Not measured | 1408 | Only Step 3.5 Flash measured |
| LMArena Text: business and finance | Not measured | 1394 | Only Step 3.5 Flash measured |
| Neither model has a result on the other 14 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | Step 3.5 Flash | 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 | Step 3.5 Flash | Leader |
|---|---|---|---|
| IFBench | Not measured | 66.5% | Only Step 3.5 Flash measured |
| Long context reasoning (AA-LCR) | 78.3% | 63.0% | Ling 3.0 Flash VL |
| LMArena Text | Not measured | 1403 | Only Step 3.5 Flash measured |
| LMArena Text: instruction following | Not measured | 1385 | Only Step 3.5 Flash measured |
| LMArena Text: creative writing | Not measured | 1357 | Only Step 3.5 Flash measured |
| LMArena Text: English | Not measured | 1417 | Only Step 3.5 Flash measured |
| LMArena Text: non-English | Not measured | 1385 | Only Step 3.5 Flash measured |
| LMArena Text: Chinese | Not measured | 1446 | Only Step 3.5 Flash measured |
| LMArena Text: German | Not measured | 1405 | Only Step 3.5 Flash measured |
| LMArena Text: Japanese | Not measured | 1353 | Only Step 3.5 Flash measured |
| LMArena Text: Korean | Not measured | 1351 | Only Step 3.5 Flash measured |
| LMArena Text: French | Not measured | 1421 | Only Step 3.5 Flash measured |
| LMArena Text: Spanish | Not measured | 1419 | Only Step 3.5 Flash measured |
| LMArena Text: Russian | Not measured | 1385 | Only Step 3.5 Flash measured |
| LMArena Text: Polish | Not measured | 1389 | Only Step 3.5 Flash measured |
| LMArena Text: multi-turn | Not measured | 1404 | Only Step 3.5 Flash measured |
| LMArena Text: longer queries | Not measured | 1402 | Only Step 3.5 Flash measured |
| LMArena Text: writing and language | Not measured | 1372 | Only Step 3.5 Flash measured |
| LMArena Text: entertainment and media | Not measured | 1360 | Only Step 3.5 Flash measured |
| Neither model has a result on the other 27 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash VL | Step 3.5 Flash | 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 | StepFun Step 3.5 Flash |
|---|---|---|
| Maker | inclusionAI | StepFun |
| Weights | Open weights | Open weights |
| Released | September 10, 2026 | January 29, 2026 |
| Context window | 131K | 262K |
| Input $/Mtok | $0.06 | $0.10 |
| Output $/Mtok | $0.18 | $0.30 |
| 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 Step 3.5 Flash 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 1.7x cheaper ($0.18 vs $0.30 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 Step 3.5 Flash?
Ling 3.0 Flash VL costs $0.06 per million input tokens and $0.18 per million output tokens; Step 3.5 Flash costs $0.10 and $0.30. Cost per solved task is known for neither of them.
Which has the bigger context window, Ling 3.0 Flash VL or Step 3.5 Flash?
Step 3.5 Flash, with 262K tokens against 131K.
How many benchmarks is the Ling 3.0 Flash VL vs Step 3.5 Flash comparison based on?
4 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 Step 3.5 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.