of Qwen3.5-9B's structured outputs fail on Together.
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.
| # | Provider | Structured outputs a day | $ in / out per M | Tokens/s | Uptime | |
|---|---|---|---|---|---|---|
| 1 | Prime Intellectbf16# | 0.30% | 107k | $0.02 / $0.03 | 78 | 99.6% |
| 2 | DeepInfrabf16# | 0.96% | 89k | $0.10 / $0.15 | 13 | 93.6% |
| 3 | Parasailbf16# | 3.26% | 163k | $0.10 / $0.25 | 67 | 99.7% |
| 4 | SiliconFlowfp8# | 5.05% | 23k | $0.10 / $0.15 | 34 | 96.3% |
| 5 | Darkbloomfp4# | 13.39% | 28k | $0.08 / $0.13 | 36 | 99.8% |
| 6 | Together# | 14.86% | 13k | $0.17 / $0.25 | 87 | 98.1% |
{
"provider": {
"order": [
"primeintellect/bf16",
"deepinfra/bf16"
],
"ignore": [
"parasail/bf16",
"siliconflow/fp8",
"darkbloom/fp4",
"together"
]
}
}Give llms.txt to your agent
And which provider to use.
Your users don't see the provider. They see your model failing.
of Qwen3.5-9B's structured outputs fail on Together.
as often on Together as on Prime Intellect (bf16), its best provider.
broken structured outputs a day across its 6 providers.
Releasing a model? Make your own API the one every provider is measured against.
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