R1 0528 vs Ling 3.0 Flash VL
Ling 3.0 Flash VL leads R1 0528 on the Artificial Analysis Intelligence Index, 24.6 to 13.1, and Ling 3.0 Flash VL costs 12.1x less per output token ($0.18 vs $2.18 per million). Updated October 23, 2026; 4 benchmarks have a result for both.
R1 0528 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 R1 0528 for a larger context window (164K against 131K tokens) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.
- Shared results
- 4
- R1 0528 only
- 59
- 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 13.1.
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
Web design
Design Arena: websites
No call
Only R1 0528 has a Design Arena: websites result, 1149.
Directional only
Long documents
Listed context window
R1 0528
R1 0528 takes 164K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash VL
R1 0528 $0.0016, Ling 3.0 Flash VL $0.0001 per turn.
List prices
At a glance
- Coding index
- R1 0528 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
- Long context reasoning (AA-LCR): R1 0528 55.7% against Ling 3.0 Flash VL 78.3%, 22.7 points apart on a 0 to 100 scale.
- Output price
- R1 0528 $2.18 against Ling 3.0 Flash VL $0.18 per million output tokens, 12.1x apart.
- Context window
- R1 0528 takes 164K 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 | R1 0528 | 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 Index9 boards, none shared
| Benchmark | R1 0528 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| Aider polyglot | 71.4% | Not measured | Only R1 0528 measured |
| AA Coding Index | Not measured | 57.0 | Only Ling 3.0 Flash VL measured |
| LiveCodeBench (Artificial Analysis run) | 77.0% | Not measured | Only R1 0528 measured |
| SciCode | Not measured | 44.2% | Only Ling 3.0 Flash VL measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | Not measured | Only R1 0528 measured |
| WeirdML | 41.6% | Not measured | Only R1 0528 measured |
| ALE-Bench | 804.1 | Not measured | Only R1 0528 measured |
| LMArena Text: coding | 1427 | Not measured | Only R1 0528 measured |
| LMArena Text: software and IT | 1435 | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | R1 0528 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Intelligence Index | 13.1 | 24.6 | 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 index5 boards, none shared
| Benchmark | R1 0528 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 28.7 | Only Ling 3.0 Flash VL measured |
| τ²-Bench Telecom | 36.5% | Not measured | Only R1 0528 measured |
| METR time horizons | 53.8% | Not measured | Only R1 0528 measured |
| DeepResearch Bench | 35.1% | Not measured | Only R1 0528 measured |
| BrowseComp-Plus | 16.4% | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | R1 0528 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 81.3% | 86.2% | Ling 3.0 Flash VL |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 22.0% | Ling 3.0 Flash VL |
| GPQA Diamond (Epoch AI run) | 76.3% | Not measured | Only R1 0528 measured |
| ARC-AGI | 21.2% | Not measured | Only R1 0528 measured |
| ARC-AGI-2 | 1.1% | Not measured | Only R1 0528 measured |
| SimpleBench | 40.8% | Not measured | Only R1 0528 measured |
| LMArena Text: hard prompts | 1415 | Not measured | Only R1 0528 measured |
| LMArena Text: expert | 1393 | Not measured | Only R1 0528 measured |
| LMArena Text: hard prompts in English | 1422 | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | R1 0528 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Math Index | 76.0 | Not measured | Only R1 0528 measured |
| AIME 2025 (Artificial Analysis run) | 76.0% | Not measured | Only R1 0528 measured |
| OTIS Mock AIME | 66.4% | Not measured | Only R1 0528 measured |
| MATH level 5 | 96.6% | Not measured | Only R1 0528 measured |
| LMArena Text: math | 1400 | Not measured | Only R1 0528 measured |
| LMArena Text: mathematical work | 1415 | Not measured | Only R1 0528 measured |
| MathArena | 12.9% | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | R1 0528 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 84.9% | Not measured | Only R1 0528 measured |
| LMArena Text: science | 1430 | Not measured | Only R1 0528 measured |
| LMArena Text: medicine and healthcare | 1445 | Not measured | Only R1 0528 measured |
| LMArena Text: legal and government | 1419 | Not measured | Only R1 0528 measured |
| LMArena Text: business and finance | 1401 | Not measured | Only R1 0528 measured |
| PRBench Finance | 32.7% | Not measured | Only R1 0528 measured |
| PRBench Legal | 36.6% | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | R1 0528 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| Design Arena: websites | 1149 | Not measured | Only R1 0528 measured |
| Design Arena: UI components | 1100 | Not measured | Only R1 0528 measured |
| Design Arena: game dev | 1097 | Not measured | Only R1 0528 measured |
| Design Arena: data viz | 1183 | Not measured | Only R1 0528 measured |
| Design Arena: 3D | 1112 | Not measured | Only R1 0528 measured |
| Design Arena: all code categories | 1138 | Not measured | Only R1 0528 measured |
| Design Arena: SVG | 1038 | Not measured | Only R1 0528 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | R1 0528 | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| IFBench | 39.6% | Not measured | Only R1 0528 measured |
| Long context reasoning (AA-LCR) | 55.7% | 78.3% | Ling 3.0 Flash VL |
| Fiction.LiveBench | 75.0% | Not measured | Only R1 0528 measured |
| Creative writing (Lech Mazur) | 81.9% | Not measured | Only R1 0528 measured |
| LMArena Text | 1428 | Not measured | Only R1 0528 measured |
| LMArena Text: instruction following | 1381 | Not measured | Only R1 0528 measured |
| LMArena Text: creative writing | 1405 | Not measured | Only R1 0528 measured |
| LMArena Text: English | 1437 | Not measured | Only R1 0528 measured |
| LMArena Text: non-English | 1412 | Not measured | Only R1 0528 measured |
| LMArena Text: Chinese | 1442 | Not measured | Only R1 0528 measured |
| LMArena Text: German | 1404 | Not measured | Only R1 0528 measured |
| LMArena Text: Japanese | 1391 | Not measured | Only R1 0528 measured |
| LMArena Text: Korean | 1359 | Not measured | Only R1 0528 measured |
| LMArena Text: French | 1417 | Not measured | Only R1 0528 measured |
| LMArena Text: Spanish | 1411 | Not measured | Only R1 0528 measured |
| LMArena Text: Russian | 1423 | Not measured | Only R1 0528 measured |
| LMArena Text: Polish | 1428 | Not measured | Only R1 0528 measured |
| LMArena Text: multi-turn | 1404 | Not measured | Only R1 0528 measured |
| LMArena Text: longer queries | 1391 | Not measured | Only R1 0528 measured |
| LMArena Text: writing and language | 1401 | Not measured | Only R1 0528 measured |
| LMArena Text: entertainment and media | 1400 | Not measured | Only R1 0528 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 | R1 0528 | 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 | DeepSeek R1 0528 | inclusionAI Ling 3.0 Flash VL |
|---|---|---|
| Maker | DeepSeek | inclusionAI |
| Weights | Open weights | Open weights |
| Released | May 28, 2025 | September 10, 2026 |
| Context window | 164K | 131K |
| Input $/Mtok | $0.50 | $0.06 |
| Output $/Mtok | $2.18 | $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 R1 0528 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 R1 0528 for a larger context window (164K against 131K tokens) and work measured by AA Intelligence Index or GPQA Diamond (Artificial Analysis run), where it leads.
Which is cheaper, R1 0528 or Ling 3.0 Flash VL?
R1 0528 costs $0.50 per million input tokens and $2.18 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, R1 0528 or Ling 3.0 Flash VL?
R1 0528, with 164K tokens against 131K.
How many benchmarks is the R1 0528 vs Ling 3.0 Flash VL comparison based on?
4 benchmarks have a result for both models as of October 23, 2026. R1 0528'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.