Ling 3.0 Flash vs MiniMax M2
Ling 3.0 Flash leads MiniMax M2 on the Artificial Analysis Intelligence Index, 20.1 to 18.6, and Ling 3.0 Flash costs 8.4x less per output token ($0.1215 vs $1.02 per million). Updated October 23, 2026; 4 benchmarks have a result for both.
Ling 3.0 Flash or MiniMax M2: which to pick
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; MiniMax M2 has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 4
- Ling 3.0 Flash only
- 20
- MiniMax M2 only
- 46
- 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
Only Ling 3.0 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Ling 3.0 Flash
Ling 3.0 Flash leads, 20.1 against 18.6.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash has a AA Agentic Index result, 19.3.
Directional only
Reasoning
GPQA Diamond
No call
Only Ling 3.0 Flash has a GPQA Diamond result, 84.8%.
Directional only
Knowledge
MMLU Pro
No call
Only Ling 3.0 Flash has a MMLU Pro result, 82.0%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M2 has a Design Arena: websites result, 1143.
Directional only
Long documents
Listed context window
Ling 3.0 Flash
Ling 3.0 Flash takes 262K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Ling 3.0 Flash $0.0001, MiniMax M2 $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Ling 3.0 Flash
Ling 3.0 Flash $0.05, MiniMax M2 $0.702.
Published attempt cost and pass rate
At a glance
- Coding index
- Ling 3.0 Flash 29.6 from 2 benchmarks, MiniMax M2 not benchmarked.
- Widest category
- Reasoning, 8.9 points apart on average over 2 shared benchmarks.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): Ling 3.0 Flash 23.7% against MiniMax M2 13.7%, 10.0 points apart on a 0 to 100 scale.
- Output price
- Ling 3.0 Flash $0.1215 against MiniMax M2 $1.02 per million output tokens, 8.4x apart.
- Context window
- Ling 3.0 Flash takes 262K tokens, MiniMax M2 205K.
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 | Bars | MiniMax M2 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 4 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index16 boards, none shared
| Benchmark | Ling 3.0 Flash | MiniMax M2 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 61.0% | Only MiniMax M2 measured |
| LMArena WebDev | Not measured | 1297 | Only MiniMax M2 measured |
| AA Coding Index | 50.6 | Not measured | Only Ling 3.0 Flash measured |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only Ling 3.0 Flash measured |
| SWE-bench Verified (Vals AI) | 65.2% | Not measured | Only Ling 3.0 Flash measured |
| Vibe Code Bench (Vals AI) | 2.9% | Not measured | Only Ling 3.0 Flash measured |
| Code migration (Vals AI) | 0.0% | Not measured | Only Ling 3.0 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | Not measured | Only Ling 3.0 Flash measured |
| SkillsBench (Vals AI) | 27.9% | Not measured | Only Ling 3.0 Flash measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 82.6% | Only MiniMax M2 measured |
| SciCode | 42.0% | Not measured | Only Ling 3.0 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 25.8% | Only MiniMax M2 measured |
| Terminal-Bench | Not measured | 30.0% | Only MiniMax M2 measured |
| LMArena Text: coding | Not measured | 1371 | Only MiniMax M2 measured |
| LMArena Text: software and IT | Not measured | 1373 | Only MiniMax M2 measured |
| LMArena WebDev: HTML | Not measured | 1306 | Only MiniMax M2 measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Ling 3.0 Flash | MiniMax M2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.1 | 18.6 | Ling 3.0 Flash |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Ling 3.0 Flash | MiniMax M2 | Leader |
|---|---|---|---|
| AA Agentic Index | 19.3 | Not measured | Only Ling 3.0 Flash measured |
| Finance Agent (Vals AI) | 30.3% | Not measured | Only Ling 3.0 Flash measured |
| Legal Research Bench (Vals AI) | 0.0% | Not measured | Only Ling 3.0 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 25.0% | Not measured | Only Ling 3.0 Flash measured |
| τ²-Bench Telecom | Not measured | 86.8% | Only MiniMax M2 measured |
| Vending-Bench 2 | Not measured | $161 | Only MiniMax M2 measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Ling 3.0 Flash | MiniMax M2 | Leader |
|---|---|---|---|
| GPQA Diamond | 84.8% | Not measured | Only Ling 3.0 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 85.5% | 77.7% | Ling 3.0 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 23.7% | 13.7% | Ling 3.0 Flash |
| LMArena Text: hard prompts | Not measured | 1357 | Only MiniMax M2 measured |
| LMArena Text: expert | Not measured | 1338 | Only MiniMax M2 measured |
| LMArena Text: hard prompts in English | Not measured | 1376 | Only MiniMax M2 measured |
| Kagi LLM Benchmark | Not measured | 57.8% | Only MiniMax M2 measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Ling 3.0 Flash | MiniMax M2 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 78.3 | Only MiniMax M2 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 78.3% | Only MiniMax M2 measured |
| LMArena Text: math | Not measured | 1351 | Only MiniMax M2 measured |
| LMArena Text: mathematical work | Not measured | 1368 | Only MiniMax M2 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Ling 3.0 Flash | MiniMax M2 | Leader |
|---|---|---|---|
| MMLU Pro | 82.0% | Not measured | Only Ling 3.0 Flash measured |
| LegalBench (Vals AI) | 79.7% | Not measured | Only Ling 3.0 Flash measured |
| CorpFin (Vals AI) | 61.9% | Not measured | Only Ling 3.0 Flash measured |
| TaxEval (Vals AI) | 70.7% | Not measured | Only Ling 3.0 Flash measured |
| MedCode (Vals AI) | 32.3% | Not measured | Only Ling 3.0 Flash measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 82.0% | Only MiniMax M2 measured |
| LMArena Text: science | Not measured | 1349 | Only MiniMax M2 measured |
| LMArena Text: medicine and healthcare | Not measured | 1367 | Only MiniMax M2 measured |
| LMArena Text: legal and government | Not measured | 1349 | Only MiniMax M2 measured |
| LMArena Text: business and finance | Not measured | 1336 | Only MiniMax M2 measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Ling 3.0 Flash | MiniMax M2 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1143 | Only MiniMax M2 measured |
| Design Arena: UI components | Not measured | 1134 | Only MiniMax M2 measured |
| Design Arena: game dev | Not measured | 1118 | Only MiniMax M2 measured |
| Design Arena: data viz | Not measured | 1140 | Only MiniMax M2 measured |
| Design Arena: 3D | Not measured | 1098 | Only MiniMax M2 measured |
| Design Arena: all code categories | Not measured | 1135 | Only MiniMax M2 measured |
| Design Arena: SVG | Not measured | 1100 | Only MiniMax M2 measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Ling 3.0 Flash | MiniMax M2 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 50.7% | Not measured | Only Ling 3.0 Flash measured |
| MedScribe (Vals AI) | 80.9% | Not measured | Only Ling 3.0 Flash measured |
| IFBench | Not measured | 72.3% | Only MiniMax M2 measured |
| Long context reasoning (AA-LCR) | 73.0% | 64.3% | Ling 3.0 Flash |
| LMArena Text | Not measured | 1340 | Only MiniMax M2 measured |
| LMArena Text: instruction following | Not measured | 1329 | Only MiniMax M2 measured |
| LMArena Text: creative writing | Not measured | 1287 | Only MiniMax M2 measured |
| LMArena Text: English | Not measured | 1364 | Only MiniMax M2 measured |
| LMArena Text: non-English | Not measured | 1313 | Only MiniMax M2 measured |
| LMArena Text: Chinese | Not measured | 1366 | Only MiniMax M2 measured |
| LMArena Text: German | Not measured | 1354 | Only MiniMax M2 measured |
| LMArena Text: French | Not measured | 1336 | Only MiniMax M2 measured |
| LMArena Text: Spanish | Not measured | 1326 | Only MiniMax M2 measured |
| LMArena Text: Russian | Not measured | 1330 | Only MiniMax M2 measured |
| LMArena Text: Polish | Not measured | 1311 | Only MiniMax M2 measured |
| LMArena Text: multi-turn | Not measured | 1361 | Only MiniMax M2 measured |
| LMArena Text: longer queries | Not measured | 1331 | Only MiniMax M2 measured |
| LMArena Text: writing and language | Not measured | 1295 | Only MiniMax M2 measured |
| LMArena Text: entertainment and media | Not measured | 1298 | Only MiniMax M2 measured |
| Neither model has a result on the other 29 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash | MiniMax M2 | 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 costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash 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 | MiniMax M2 |
|---|---|---|
| Maker | inclusionAI | MiniMax |
| Weights | Open weights | Open weights |
| Released | July 23, 2026 | October 23, 2025 |
| Context window | 262K | 205K |
| Input $/Mtok | $0.0405 | $0.255 |
| Output $/Mtok | $0.1215 | $1.02 |
| Coding index | 29.6 | Not benchmarked |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $0.05 | $0.702 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ling 3.0 Flash better than MiniMax M2 for coding?
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; MiniMax M2 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Ling 3.0 Flash or MiniMax M2?
Ling 3.0 Flash costs $0.0405 per million input tokens and $0.1215 per million output tokens; MiniMax M2 costs $0.255 and $1.02. Per solved SWE-bench Verified task, Ling 3.0 Flash costs $0.05 and MiniMax M2 $0.702.
Which has the bigger context window, Ling 3.0 Flash or MiniMax M2?
Ling 3.0 Flash, with 262K tokens against 205K.
How many benchmarks is the Ling 3.0 Flash vs MiniMax M2 comparison based on?
4 benchmarks have a result for both models as of October 23, 2026. Ling 3.0 Flash's coding index rests on 2 independent benchmarks and MiniMax M2's on 1. Where only one model has a result, the page says so instead of naming a winner.