of GLM 5.3's structured outputs fail on inference.net (fp4).
The same model breaks your pipeline's structured outputs 15× more often on some inference providers than on others. Find the best one for your pipelines.
| # | Model | Broken structured outputs | Rank | Best for this model | Structured outputs a day |
|---|---|---|---|---|---|
| 1 | DeepSeek V4.1 Flash 1017fp8 | 0.70% | 3 of 33 | Reka AI 0.40% | 2.8M |
| 2 | DeepSeek V4.1 Flashfp8 | 0.80% | 7 of 28 | DeepInfra (fp8/flex) 0.35% | 3.0M |
| 3 | MiniMax M3.1 Flashfp4 | 1.13% | 6 of 8 | Nebius Token Factory (fp4) 0.14% | 11k |
| 4 | GLM 5.3 Flashfp4 | 1.48% | 20 of 29 | Parasail (fp4) 0.28% | 1.3M |
| 5 | Kimi K3fp4/fast | 2.04% | 11 of 20 | Parasail (fp4) 0.20% | 39k |
| 6 | Kimi K3fp4 | 3.11% | 15 of 20 | Parasail (fp4) 0.20% | 37k |
| 7 | GLM 5.3fp4 | 6.90% | 23 of 28 | Together 0.25% | 83k |
And which provider to use.
The same provider can handle structured outputs well on one model and struggle on the next. Implementations diverge on strings, optionals, composition and conditionals (the April announcement): the schema one provider enforces, another ignores.
of GLM 5.3's structured outputs fail on inference.net (fp4).
on DeepSeek V4.1 Flash 1017, its best model.
models, where the settings tell OpenRouter to skip inference.net.
dotjson plugs into your inference stack, so every model you serve gets perfect structured outputs from day 0.
Fix inference.net's structured outputs↵