Nemotron 3.5 Lightning 30B A3B vs Schematron V2 Small

Nemotron 3.5 Lightning 30B A3B is the better all-round choice, scoring 68/100 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.

Nemotron 3.5 Lightning 30B A3B is cheaper at $0.055 input / $0.20 output per million tokens (median across 10 API providers; free on Nvidia). 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 $0.091 per million tokens for Nemotron 3.5 Lightning 30B A3B versus $0.095 for Schematron V2 Small (1× as much).

There is no independent benchmark that covers both models yet. Nemotron 3.5 Lightning 30B A3B has not been scored yet and Schematron V2 Small has not been scored yet.

There are no published SWE-bench Verified results for Nemotron 3.5 Lightning 30B A3B 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.

Nemotron 3.5 Lightning 30B A3B has the largest context window at 262,144 tokens, against 128,000 for Schematron V2 Small. Maximum output per response: Nemotron 3.5 Lightning 30B A3B up to 262,144, Schematron V2 Small up to 4,096 tokens.

Nemotron 3.5 Lightning 30B A3B accepts text; Schematron V2 Small accepts text. They handle the same number of input types.

Nemotron 3.5 Lightning 30B A3B publishes its weights and can be self-hosted; Schematron V2 Small is proprietary.

Nemotron 3.5 Lightning 30B A3B is the newest, released Aug 11, 2026. Schematron V2 Small came out Apr 16, 2026. Knowledge cutoff: Nemotron 3.5 Lightning 30B A3B Sep 2025.

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.