Ling 3.0 Flash vs Schematron V2 Small
Ling 3.0 Flash comes out ahead, 65 to 52 on our weighted score, and it is the cheaper option too.
- Our pick
inclusionAILing 3.0 Flash
65/100- ECI—
- Price$0.06 / $0.18
- Context262K
Inference.net
Schematron V2 Small
52/100- ECI—
- Price$0.05 / $0.23
- Context128K
Add a model
Make it a three-way comparison.
Ling 3.0 Flash is our pick
Ling 3.0 Flash is the better all-round choice, scoring 65/100 against Schematron V2 Small (52). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceLing 3.0 FlashLing 3.0 Flash $0.09 · Schematron V2 Small $0.095 per 1M tokens (3:1 blend)
- Longest contextLing 3.0 FlashLing 3.0 Flash 262,144 · Schematron V2 Small 128,000 tokens
- Widest inputsSame inputsLing 3.0 Flash: Text · Schematron V2 Small: Text
- Self-hostingLing 3.0 FlashPublishes downloadable weights (MIT)
| Measure | Weight | Ling 3.0 Flash | Schematron V2 Small |
|---|---|---|---|
| Price | 50% | 95 | 94 |
| Inputs & features | 30% | 35 | 0 |
| Context window | 20% | 37 | 24 |
| Overall | 100% | 65/100 | 52/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Ling 3.0 FlashinclusionAI | Schematron V2 SmallInference.net |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.06 | $0.05 (best) |
| Output | $0.18 (best) | $0.23 |
| Cached input | — | — |
| Blended (3:1) | $0.09 (best) | $0.095 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 7 providers | Median of 5 providers |
| Limits | ||
| Context window | 262,144 tokens (best) | 128,000 tokens |
| Max output | 32,768 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | No |
| Structured output | No | No |
| Availability | ||
| Weights | OpenMIT | Proprietary |
| API model ID | — | — |
| API providers | 9 (best) | 5 |
| Released | Jul 23, 2026 | Apr 16, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Ling 3.0 Flash$0.96
- Schematron V2 Small$0.96
Which should you choose?
Which is better: Ling 3.0 Flash or Schematron V2 Small?
Ling 3.0 Flash is the better all-round choice, scoring 65/100 against Schematron V2 Small (52). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Ling 3.0 Flash or Schematron V2 Small?
Ling 3.0 Flash is cheaper at $0.06 input / $0.18 output per million tokens (median across 7 API providers). Schematron V2 Small costs $0.05 input / $0.23 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.09 per million tokens for Ling 3.0 Flash versus $0.095 for Schematron V2 Small (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Ling 3.0 Flash has not been scored yet and Schematron V2 Small has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Ling 3.0 Flash and Schematron V2 Small yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Schematron V2 Small does not support tool calling, which most coding agents need.
Which has the bigger context window?
Ling 3.0 Flash has the largest context window at 262,144 tokens, against 128,000 for Schematron V2 Small. Maximum output per response: Ling 3.0 Flash up to 32,768, Schematron V2 Small up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Ling 3.0 Flash accepts text; Schematron V2 Small accepts text. They handle the same number of input types.
Are any of these open source?
Ling 3.0 Flash publishes its weights (MIT) and can be self-hosted; Schematron V2 Small is proprietary.
Which is newer?
Ling 3.0 Flash is the newest, released Jul 23, 2026. Schematron V2 Small came out Apr 16, 2026.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
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