GPT-4.1 Mini vs Ling 3.0 Flash VL
Ling 3.0 Flash VL leads GPT-4.1 Mini on the Artificial Analysis Intelligence Index, 24.6 to 10.2, and Ling 3.0 Flash VL costs 8.9x less per output token ($0.18 vs $1.60 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
GPT-4.1 Mini 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 GPT-4.1 Mini for a larger context window (1.05M against 131K tokens) and work measured by AA Coding Index or AA Intelligence Index, where it leads.
- Shared results
- 5
- GPT-4.1 Mini only
- 83
- Ling 3.0 Flash VL only
- 2
- Like-for-like categories
- 4 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 10.2.
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 GPT-4.1 Mini has a GPQA Diamond result, 67.9%.
Directional only
Math
AIME
No call
Only GPT-4.1 Mini has a AIME result, 49.4%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4.1 Mini has a MMLU Pro result, 77.2%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-4.1 Mini has a Design Arena: websites result, 997.
Directional only
Long documents
Listed context window
GPT-4.1 Mini
GPT-4.1 Mini takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash VL
GPT-4.1 Mini $0.0012, Ling 3.0 Flash VL $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-4.1 Mini has the number, $1.818.
Directional only
At a glance
- Coding index
- GPT-4.1 Mini not benchmarked, Ling 3.0 Flash VL not benchmarked.
- Widest category
- Coding, 36.8 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Coding Index: GPT-4.1 Mini 20.2 against Ling 3.0 Flash VL 57.0, 36.8 points apart on a 0 to 100 scale.
- Output price
- GPT-4.1 Mini $1.60 against Ling 3.0 Flash VL $0.18 per million output tokens, 8.9x apart.
- Context window
- GPT-4.1 Mini 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 | GPT-4.1 Mini | Bars | Ling 3.0 Flash VL | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | GPT-4.1 Mini | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| Aider polyglot | 32.4% | Not measured | Only GPT-4.1 Mini measured |
| SWE-bench Verified | 23.9% | Not measured | Only GPT-4.1 Mini measured |
| AA Coding Index | 20.2 | 57.0 | Ling 3.0 Flash VL |
| LiveCodeBench (Vals AI) | 58.2% | Not measured | Only GPT-4.1 Mini measured |
| LiveCodeBench (Artificial Analysis run) | 48.3% | Not measured | Only GPT-4.1 Mini measured |
| SciCode | Not measured | 44.2% | Only Ling 3.0 Flash VL measured |
| Terminal-Bench Hard (Artificial Analysis run) | 7.6% | Not measured | Only GPT-4.1 Mini measured |
| WeirdML | 37.6% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: coding | 1367 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: software and IT | 1360 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 Mini | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.2 | 24.6 | Ling 3.0 Flash VL |
| Epoch Capabilities Index | 134.9 | Not measured | Only GPT-4.1 Mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-4.1 Mini | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 28.7 | Only Ling 3.0 Flash VL measured |
| τ²-Bench Telecom | 52.9% | Not measured | Only GPT-4.1 Mini measured |
| Berkeley Function Calling Leaderboard (BFCL) | 50.4% | Not measured | Only GPT-4.1 Mini 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 | GPT-4.1 Mini | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| GPQA Diamond | 67.9% | Not measured | Only GPT-4.1 Mini measured |
| MMMU Pro (Vals AI) | 70.5% | Not measured | Only GPT-4.1 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 66.4% | 86.2% | Ling 3.0 Flash VL |
| Humanity's Last Exam (Artificial Analysis run) | 5.0% | 22.0% | Ling 3.0 Flash VL |
| GPQA Diamond (Epoch AI run) | 65.8% | Not measured | Only GPT-4.1 Mini measured |
| ARC-AGI | 3.5% | Not measured | Only GPT-4.1 Mini measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4.1 Mini measured |
| Chess puzzles | 1.0% | Not measured | Only GPT-4.1 Mini measured |
| Mystery game puzzles | 7.0% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: hard prompts | 1349 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: expert | 1338 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: hard prompts in English | 1362 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: diagrams | 1182 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: homework | 1214 | Not measured | Only GPT-4.1 Mini measured |
| Kagi LLM Benchmark | 48.6% | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 8 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | GPT-4.1 Mini | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| AIME | 49.4% | Not measured | Only GPT-4.1 Mini measured |
| MATH 500 (Vals AI) | 88.0% | Not measured | Only GPT-4.1 Mini measured |
| MGSM (Vals AI) | 87.8% | Not measured | Only GPT-4.1 Mini measured |
| AA Math Index | 46.3 | Not measured | Only GPT-4.1 Mini measured |
| AIME 2025 (Artificial Analysis run) | 46.3% | Not measured | Only GPT-4.1 Mini measured |
| OTIS Mock AIME | 44.7% | Not measured | Only GPT-4.1 Mini measured |
| FrontierMath, tiers 1 to 3 | 6.7% | Not measured | Only GPT-4.1 Mini measured |
| MATH level 5 | 87.3% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: math | 1343 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: mathematical work | 1347 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | GPT-4.1 Mini | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| MMLU Pro | 77.2% | Not measured | Only GPT-4.1 Mini measured |
| LegalBench (Vals AI) | 78.0% | Not measured | Only GPT-4.1 Mini measured |
| CorpFin (Vals AI) | 57.9% | Not measured | Only GPT-4.1 Mini measured |
| TaxEval (Vals AI) | 71.9% | Not measured | Only GPT-4.1 Mini measured |
| MortgageTax (Vals AI) | 65.5% | Not measured | Only GPT-4.1 Mini measured |
| MedQA (Vals AI) | 84.6% | Not measured | Only GPT-4.1 Mini measured |
| MMLU Pro (Artificial Analysis run) | 78.1% | Not measured | Only GPT-4.1 Mini measured |
| SimpleQA Verified | 12.7% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: science | 1328 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: medicine and healthcare | 1324 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: legal and government | 1343 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: business and finance | 1322 | Not measured | Only GPT-4.1 Mini measured |
| PRBench Finance | 30.4% | Not measured | Only GPT-4.1 Mini measured |
| PRBench Legal | 30.4% | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-4.1 Mini | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| Design Arena: websites | 997 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: UI components | 959 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: game dev | 1070 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: data viz | 1034 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: 3D | 836 | Not measured | Only GPT-4.1 Mini measured |
| Design Arena: all code categories | 993 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-4.1 Mini | Ling 3.0 Flash VL | Leader |
|---|---|---|---|
| IFBench | 38.3% | Not measured | Only GPT-4.1 Mini measured |
| Long context reasoning (AA-LCR) | 44.0% | 78.3% | Ling 3.0 Flash VL |
| DTBench | 68.8% | Not measured | Only GPT-4.1 Mini measured |
| LMCA | 21.1% | Not measured | Only GPT-4.1 Mini measured |
| Fiction.LiveBench | 44.4% | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text | 1341 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: instruction following | 1333 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: creative writing | 1299 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision | 1181 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: English | 1356 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: non-English | 1318 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Chinese | 1329 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: German | 1350 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Japanese | 1290 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Korean | 1298 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: French | 1358 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Spanish | 1319 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Russian | 1324 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: Polish | 1326 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: multi-turn | 1354 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: longer queries | 1344 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: writing and language | 1319 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Text: entertainment and media | 1300 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: English | 1191 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: Chinese | 1186 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: reading text | 1188 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: humor | 1182 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: captioning | 1174 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: recognizing things | 1187 | Not measured | Only GPT-4.1 Mini measured |
| LMArena Vision: creative writing | 1182 | Not measured | Only GPT-4.1 Mini measured |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-4.1 Mini | 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 | OpenAI GPT-4.1 Mini | inclusionAI Ling 3.0 Flash VL |
|---|---|---|
| Maker | OpenAI | inclusionAI |
| Weights | No public weights listed | Open weights |
| Released | April 14, 2025 | September 10, 2026 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.40 | $0.06 |
| Output $/Mtok | $1.60 | $0.18 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | $1.818 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4.1 Mini 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 GPT-4.1 Mini for a larger context window (1.05M against 131K tokens) and work measured by AA Coding Index or AA Intelligence Index, where it leads.
Which is cheaper, GPT-4.1 Mini or Ling 3.0 Flash VL?
GPT-4.1 Mini costs $0.40 per million input tokens and $1.60 per million output tokens; Ling 3.0 Flash VL costs $0.06 and $0.18. Cost per solved task is known for GPT-4.1 Mini only.
Which has the bigger context window, GPT-4.1 Mini or Ling 3.0 Flash VL?
GPT-4.1 Mini, with 1.05M tokens against 131K.
How many benchmarks is the GPT-4.1 Mini vs Ling 3.0 Flash VL comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. GPT-4.1 Mini'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.