of Qwen3.5-9B's structured outputs fail on Together.
Updated October 31, 2026 · How we measure
Structured-output index
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.
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| # | Model | Broken structured outputs | Rank | Best for this model | Structured outputs a day |
|---|---|---|---|---|---|
| 1 | GLM 5.3 | 0.25% | 1 of 28 | — | 53k |
| 2 | Qwen3.8 2.4T A95B | 0.48% | 1 of 2 | — | 5.7k |
| 3 | GLM 5.3 Flash | 0.51% | 6 of 29 | Parasail (fp4) 0.28% | 26.6M |
| 4 | GLM 5.2 | 0.59% | 2 of 22 | Venice (fp8) 0.23% | 36k |
| 5 | Muse Spark Open | 0.68% | 1 of 4 | — | 5.9k |
| 6 | Kimi K3 | 0.73% | 5 of 20 | Parasail (fp4) 0.20% | 28k |
| 7 | DeepSeek V4 Pro 0813 | 0.83% | 4 of 13 | Cloudflare 0.39% | 9.6k |
| 8 | DeepSeek V4.1 Flash 1017 | 1.05% | 13 of 33 | Reka AI 0.40% | 1.4M |
| 9 | MiniMax M3.1 Flash | 1.06% | 5 of 8 | Nebius Token Factory (fp4) 0.14% | 36k |
| 10 | DeepSeek V4.1 Flash | 1.93% | 16 of 28 | DeepInfra (fp8/flex) 0.35% | 1.5M |
| 11 | gpt-oss-120b | 2.02% | 11 of 18 | MARA 0.76% | 17k |
| 12 | MiniMax M3 | 2.57% | 2 of 3 | CoreWeave (fp4) 0.61% | 18k |
| 13 | Nemotron 3.5 Super VL | 2.64% | 4 of 6 | Venice (fp4) 1.45% | 68k |
| 14 | Qwen3.5-9B | 14.86% | 6 of 6 | Prime Intellect (bf16) 0.30% | 13k |
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And which provider to use.
For inference providers
Structured outputs don't have to break
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.
on GLM 5.3, its best model.
models, where the settings tell OpenRouter to skip Together.
dotjson plugs into your inference stack, so every model you serve gets perfect structured outputs from day 0.
Fix Together's structured outputs↵