Ling 3.0 Flash vs MiniMax M3.1 Flash
MiniMax M3.1 Flash leads Ling 3.0 Flash on coding, 59.1 to 29.6 on the Vibe Coding Index, and Ling 3.0 Flash costs 4.9x less per output token ($0.1215 vs $0.60 per million). Updated October 23, 2026; 6 benchmarks have a result for both.
Ling 3.0 Flash or MiniMax M3.1 Flash: which to pick
Pick MiniMax M3.1 Flash for coding: it scores 59.1 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash.
Pick Ling 3.0 Flash for output tokens 4.9x cheaper ($0.1215 vs $0.60 per million).
- Shared results
- 6
- Ling 3.0 Flash only
- 18
- MiniMax M3.1 Flash only
- 14
- Like-for-like categories
- 5 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
MiniMax M3.1 Flash
MiniMax M3.1 Flash scores 59.1 against 29.6.
2 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiniMax M3.1 Flash
MiniMax M3.1 Flash leads, 42.7 against 20.1.
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
General
Vals Index
No call
Only MiniMax M3.1 Flash has a Vals Index result, 53.8%.
Directional only
Long documents
Listed context window
MiniMax M3.1 Flash
MiniMax M3.1 Flash takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Ling 3.0 Flash $0.0001, MiniMax M3.1 Flash $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Ling 3.0 Flash has the number, $0.05.
Directional only
At a glance
- Coding index
- Ling 3.0 Flash 29.6 from 2 benchmarks, MiniMax M3.1 Flash 59.1 from 4 benchmarks.
- Widest category
- Coding, 41.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Ling 3.0 Flash 2.9% against MiniMax M3.1 Flash 73.9%, 71.0 points apart on a 0 to 100 scale.
- Output price
- Ling 3.0 Flash $0.1215 against MiniMax M3.1 Flash $0.60 per million output tokens, 4.9x apart.
- Context window
- Ling 3.0 Flash takes 262K tokens, MiniMax M3.1 Flash 1.05M.
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 M3.1 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 6 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Ling 3.0 Flash | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 83.9% | Only MiniMax M3.1 Flash measured |
| LMArena WebDev | Not measured | 1590 | Only MiniMax M3.1 Flash 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 |
| Terminal-Bench 4 (Vals AI) | Not measured | 25.3% | Only MiniMax M3.1 Flash measured |
| Vibe Code Bench (Vals AI) | 2.9% | 73.9% | MiniMax M3.1 Flash |
| 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 |
| SciCode | 42.0% | 53.4% | MiniMax M3.1 Flash |
| LMArena WebDev: React | Not measured | 1614 | Only MiniMax M3.1 Flash measured |
| LMArena WebDev: HTML | Not measured | 1532 | Only MiniMax M3.1 Flash measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.1 | 42.7 | MiniMax M3.1 Flash |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 19.3 | Not measured | Only Ling 3.0 Flash measured |
| LiveBench research | Not measured | 72.7% | Only MiniMax M3.1 Flash measured |
| LiveBench browser | Not measured | 92.0% | Only MiniMax M3.1 Flash measured |
| LiveBench long agentic | Not measured | 34.7% | Only MiniMax M3.1 Flash measured |
| Finance Agent (Vals AI) | 30.3% | Not measured | Only Ling 3.0 Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.1% | Only MiniMax M3.1 Flash measured |
| Legal Research Bench (Vals AI) | 0.0% | 34.1% | MiniMax M3.1 Flash |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 7.5% | Only MiniMax M3.1 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 25.0% | Not measured | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 84.8% | Not measured | Only Ling 3.0 Flash measured |
| LiveBench reasoning | Not measured | 82.9% | Only MiniMax M3.1 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 85.5% | Not measured | Only Ling 3.0 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.7% | 48.0% | MiniMax M3.1 Flash |
| 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 | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 14 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Ling 3.0 Flash | MiniMax M3.1 Flash | 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 |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Ling 3.0 Flash | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| LiveBench design | Not measured | 74.0% | Only MiniMax M3.1 Flash measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | MiniMax M3.1 Flash | Leader |
|---|---|---|---|
| Vals Index | Not measured | 53.8% | Only MiniMax M3.1 Flash measured |
| LiveBench data analysis | Not measured | 71.4% | Only MiniMax M3.1 Flash measured |
| 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 |
| Long context reasoning (AA-LCR) | 73.0% | 79.7% | MiniMax M3.1 Flash |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 Flash | MiniMax M3.1 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 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 M3.1 Flash |
|---|---|---|
| Maker | inclusionAI | MiniMax |
| Weights | Open weights | Open weights |
| Released | July 23, 2026 | October 19, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.0405 | $0.15 |
| Output $/Mtok | $0.1215 | $0.60 |
| Coding index | 29.6 | 59.1 |
| Independent measurements behind it | 2 | 4 |
| Cost per solved task | $0.05 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ling 3.0 Flash better than MiniMax M3.1 Flash for coding?
Pick MiniMax M3.1 Flash for coding: it scores 59.1 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash. Pick Ling 3.0 Flash for output tokens 4.9x cheaper ($0.1215 vs $0.60 per million).
Which is cheaper, Ling 3.0 Flash or MiniMax M3.1 Flash?
Ling 3.0 Flash costs $0.0405 per million input tokens and $0.1215 per million output tokens; MiniMax M3.1 Flash costs $0.15 and $0.60. Cost per solved task is known for Ling 3.0 Flash only.
Which has the bigger context window, Ling 3.0 Flash or MiniMax M3.1 Flash?
MiniMax M3.1 Flash, with 1.05M tokens against 262K.
How many benchmarks is the Ling 3.0 Flash vs MiniMax M3.1 Flash comparison based on?
6 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 M3.1 Flash's on 4. Where only one model has a result, the page says so instead of naming a winner.