of Gemma 4 26B A4B's structured outputs fail on Google Vertex.
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# | 0.23% | 334k | $0.02 / $0.05 | 59 | 100.0% |
| 2 | AkashMLfp4# | 0.30% | 473k | $0.07 / $0.24 | 90 | 99.5% |
| 3 | DeepInfrafp8# | 0.40% | 375k | $0.07 / $0.34 | 66 | 99.9% |
| 4 | CoreWeavebf16# | 0.41% | 275k | $0.10 / $0.30 | 66 | 100.0% |
| 5 | Makora# | 0.46% | 1.1M | $0.07 / $0.24 | 158 | 100.0% |
| 6 | Parasailbf16# | 0.55% | 540k | $0.13 / $0.40 | 62 | 100.0% |
| 7 | Venicebf16# | 0.84% | 132k | $0.13 / $0.40 | 73 | 100.0% |
| 8 | NextBitbf16# | 0.94% | 3.5M | $0.07 / $0.23 | 73 | 100.0% |
| 9 | SiliconFlowfp8# | 2.05% | 74k | $0.14 / $0.40 | 48 | 94.1% |
| 10 | Darkbloom# | 3.06% | 2.2M | $0.02 / $0.10 | 47 | 99.1% |
| 11 | Google Vertex# | 7.49% | 323k | $0.15 / $0.60 | — | 95.0% |
{
"provider": {
"order": [
"primeintellect/bf16",
"akashml/fp4",
"deepinfra/fp8"
],
"ignore": [
"darkbloom",
"google-vertex/global"
]
}
}Give llms.txt to your agent
And which provider to use.
Your users don't see the provider. They see your model failing.
of Gemma 4 26B A4B's structured outputs fail on Google Vertex.
as often on Google Vertex as on Prime Intellect (bf16), its best provider.
broken structured outputs a day across its 11 providers.
Releasing a model? Make your own API the one every provider is measured against.
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