Ling 3.1 Flash vs Schematron V2 Small
Ling 3.1 Flash and Schematron V2 Small cost about the same per output token ($0.225 vs $0.23 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.225
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.23
Ling 3.1 Flash or Schematron V2 Small: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Ling 3.1 Flash for output tokens 1.0x cheaper ($0.225 vs $0.23 per million) and a larger context window (262K against 128K tokens).
No benchmark has tested both yet. Ling 3.1 Flash has results on SciCode, AA Intelligence Index and Humanity's Last Exam (Artificial Analysis run); Schematron V2 Small 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Ling 3.1 Flash has a AA Intelligence Index result, 41.1.
Directional only
Long documents
Listed context window
Ling 3.1 Flash
Ling 3.1 Flash takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Schematron V2 Small
Ling 3.1 Flash $0.0002, Schematron V2 Small $0.0002 per turn.
List prices
At a glance
- Coding index
- Ling 3.1 Flash not benchmarked, Schematron V2 Small 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 3.1 Flash $0.225 against Schematron V2 Small $0.23 per million output tokens, 1.0x apart.
- Context window
- Ling 3.1 Flash takes 262K tokens, Schematron V2 Small 128K.
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 Index1 board measured
| Benchmark | Ling 3.1 Flash | Schematron V2 Small | Leader |
|---|---|---|---|
| SciCode | 54.1% | Not measured | Only Ling 3.1 Flash measured |
| Neither model has a result on the other 38 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Ling 3.1 Flash | Schematron V2 Small | Leader |
|---|---|---|---|
| AA Intelligence Index | 41.1 | Not measured | Only Ling 3.1 Flash measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Ling 3.1 Flash | Schematron V2 Small | Leader |
|---|---|---|---|
| Humanity's Last Exam (Artificial Analysis run) | 39.4% | Not measured | Only Ling 3.1 Flash measured |
| Neither model has a result on the other 21 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Ling 3.1 Flash | Schematron V2 Small | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | 83.0% | Not measured | Only Ling 3.1 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
Schematron V2 Small costs less
Repository review
50K input + 3K output tokens
Schematron V2 Small costs less
Agent loop
200K input + 10K output tokens
Schematron V2 Small 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 3.1 Flash | Inference.net Schematron V2 Small |
|---|---|---|
| Maker | inclusionAI | Inference.net |
| Weights | No public weights listed | Open weights |
| Released | October 2, 2026 | September 12, 2026 |
| Context window | 262K | 128K |
| Input $/Mtok | $0.075 | $0.05 |
| Output $/Mtok | $0.225 | $0.23 |
| 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 Ling 3.1 Flash better than Schematron V2 Small for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Ling 3.1 Flash for output tokens 1.0x cheaper ($0.225 vs $0.23 per million) and a larger context window (262K against 128K tokens).
Which is cheaper, Ling 3.1 Flash or Schematron V2 Small?
Ling 3.1 Flash costs $0.075 per million input tokens and $0.225 per million output tokens; Schematron V2 Small costs $0.05 and $0.23. Cost per solved task is known for neither of them.
Which has the bigger context window, Ling 3.1 Flash or Schematron V2 Small?
Ling 3.1 Flash, with 262K tokens against 128K.
Has any benchmark tested both Ling 3.1 Flash and Schematron V2 Small?
No benchmark has tested both yet. Ling 3.1 Flash has results on SciCode, AA Intelligence Index and Humanity's Last Exam (Artificial Analysis run); Schematron V2 Small has none yet. Compare them on price and context instead. Data as of October 22, 2026.