Ling 3.0 Flash vs MiniMax M2-her
Ling 3.0 Flash costs 9.9x less per output token than MiniMax M2-her ($0.1215 vs $1.20 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- 29.6
- Overall
- No data
- Output $/M
- $0.1215
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.20
Ling 3.0 Flash or MiniMax M2-her: which to pick
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; MiniMax M2-her has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Ling 3.0 Flash has results on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); MiniMax M2-her has none yet. Compare them on price and context instead.
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
No call
Only Ling 3.0 Flash has a AA Intelligence Index result, 20.1.
Directional only
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
Long documents
Listed context window
Ling 3.0 Flash
Ling 3.0 Flash takes 262K tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Ling 3.0 Flash $0.0001, MiniMax M2-her $0.0009 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 M2-her not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Ling 3.0 Flash $0.1215 against MiniMax M2-her $1.20 per million output tokens, 9.9x apart.
- Context window
- Ling 3.0 Flash takes 262K tokens, MiniMax M2-her 66K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards measured
| Benchmark | Ling 3.0 Flash | MiniMax M2-her | Leader |
|---|---|---|---|
| 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 |
| SciCode | 42.0% | Not measured | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Ling 3.0 Flash | MiniMax M2-her | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.1 | Not measured | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Ling 3.0 Flash | MiniMax M2-her | 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 |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Ling 3.0 Flash | MiniMax M2-her | Leader |
|---|---|---|---|
| GPQA Diamond | 84.8% | Not measured | Only Ling 3.0 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% | Not measured | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 20 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Ling 3.0 Flash | MiniMax M2-her | 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 | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Ling 3.0 Flash | MiniMax M2-her | 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 |
| Long context reasoning (AA-LCR) | 73.0% | Not measured | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 45 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-her |
|---|---|---|
| Maker | inclusionAI | MiniMax |
| Weights | Open weights | No public weights listed |
| Released | July 23, 2026 | January 23, 2026 |
| Context window | 262K | 66K |
| Input $/Mtok | $0.0405 | $0.30 |
| Output $/Mtok | $0.1215 | $1.20 |
| Coding index | 29.6 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | $0.05 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ling 3.0 Flash better than MiniMax M2-her for coding?
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; MiniMax M2-her 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-her?
Ling 3.0 Flash costs $0.0405 per million input tokens and $0.1215 per million output tokens; MiniMax M2-her costs $0.30 and $1.20. Cost per solved task is known for Ling 3.0 Flash only.
Which has the bigger context window, Ling 3.0 Flash or MiniMax M2-her?
Ling 3.0 Flash, with 262K tokens against 66K.
Has any benchmark tested both Ling 3.0 Flash and MiniMax M2-her?
No benchmark has tested both yet. Ling 3.0 Flash has results on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); MiniMax M2-her has none yet. Compare them on price and context instead. Data as of October 22, 2026.