Best inference provider for structured extraction and JSON mode
What the benchmark found. Fireworks AI, Modal, and Telnyx tied for the task-success lead at 100.0%. The leading score represents approximately 200 exact successful results from 200 requests; operational failure rates were Fireworks AI 0.0%; Modal 0.0%; Telnyx 0.0%. The table is based on 200 ten-field contract extractions per provider and requires an exact typed object.
What this page compares. This page isolates 200 contract-term extraction requests per provider. Every answer must be valid JSON and contain ten required fields with the correct types and values, so the table measures usable structured extraction rather than whether an endpoint merely accepts a JSON-mode parameter.
How to read the result. Lead with exact task success when extracted fields flow into another system. A plausible partial object does not count as successful. Use failure rate to identify delivery problems and E2E P99 to compare how long a synchronous extraction waits once providers clear the required quality bar.
Workload and configuration. Every provider received the same 600 deliberately easy structured tasks: 200 meeting-note lookups, 200 ticket-triage classifications, and 200 contract-term extractions. GLM 5.3 Flash ran with streaming enabled, reasoning low, temperature 0, top-p 1, a 256-token output ceiling, one attempt, a 20-second timeout, and per-provider concurrency one.
Task-specific table. The table below uses only the published contract-terms-extraction aggregate rather than the three-family pooled summary. Each provider therefore contributes 200 submitted requests to this view.
APIs used. The runner called each provider's OpenAI-compatible chat-completions surface. Fireworks AI, Modal, Telnyx, Together AI, Parasail, Z.AI, Novita AI, DeepInfra, Baseten, and Nebius used the model identifiers below; the links open the provider documentation used to verify each adapter.
- Fireworks AI:
accounts/fireworks/models/glm-5p3-flash· API docs ↗ - Modal:
zai-org/GLM-5.3-Flash· API docs ↗ - Telnyx:
zai-org/GLM-5.3-Flash· API docs ↗ - Together AI:
zai-org/GLM-5.3-Flash· API docs ↗ - Parasail:
zai-org/GLM-5.3-Flash· API docs ↗ - Z.AI:
glm-5.3-flash· API docs ↗ - Novita AI:
zai-org/glm-5.3-flash· API docs ↗ - DeepInfra:
zai-org/GLM-5.3-Flash· API docs ↗ - Baseten:
zai-org/GLM-5.3-Flash· API docs ↗ - Nebius:
zai-org/GLM-5.3-Flash· API docs ↗
Providers sorted by exact contract-extraction success
The rows use only contract-term extraction aggregates. Exact successes are out of 200 complete schemas; E2E tail latency and operational failures remain visible without copying the pooled leaderboard.
| Provider / API | Task success | Exact successes | Failure rate | E2E P99 |
|---|---|---|---|---|
| Fireworks AIaccounts/fireworks/models/glm-5p3-flash ↗ | 100.0% | 200 / 200 | 0.0% | 11.9 s |
| Modalzai-org/GLM-5.3-Flash ↗ | 100.0% | 200 / 200 | 0.0% | 3.37 s |
| Telnyxzai-org/GLM-5.3-Flash ↗ | 100.0% | 200 / 200 | 0.0% | 3.48 s |
| Together AIzai-org/GLM-5.3-Flash ↗ | 98.5% | 197 / 200 | 1.5% | 6.13 s |
| Parasailzai-org/GLM-5.3-Flash ↗ | 97.5% | 195 / 200 | 2.5% | 12.2 s |
| Z.AIglm-5.3-flash ↗ | 96.0% | 192 / 200 | 0.0% | 8.74 s |
| Novita AIzai-org/glm-5.3-flash ↗ | 93.0% | 186 / 200 | 3.0% | 8.99 s |
| DeepInfrazai-org/GLM-5.3-Flash ↗ | 92.0% | 184 / 200 | 8.0% | 19.8 s |
| Basetenzai-org/GLM-5.3-Flash ↗ | 90.0% | 180 / 200 | 0.0% | 4.55 s |
| Nebiuszai-org/GLM-5.3-Flash ↗ | 85.5% | 171 / 200 | 14.5% | 13.8 s |
Structured data workflows represented by the schema
- Contract metadata extraction. Extract effective dates, renewal terms, payment terms, notice periods, and termination rights into typed fields.
- JSON tool arguments. Require every key and type before passing model output to deterministic application code.
- Document-to-record automation. Treat exact-object success as the usable yield when a response populates a database or review form.
Structured extraction and JSON-mode questions
Which provider returned the most exact contract JSON objects?
Fireworks AI, Modal, and Telnyx tied for the task-success lead at 100.0%. The leading score represents approximately 200 exact successful results from 200 requests; operational failure rates were Fireworks AI 0.0%; Modal 0.0%; Telnyx 0.0%. The table is based on 200 ten-field contract extractions per provider and requires an exact typed object.
Does a partially correct extraction receive task-success credit?
Contract extraction counts only when every required field is present and typed correctly; strings and enums compare exactly, dates use ISO YYYY-MM-DD, and the full object must match. Correct-field diagnostics do not create partial task-success credit.
Why can JSON-mode results vary when every provider serves the same model?
Even with the same requested model, delivery layers can differ in truncation, malformed output, model routing, stream completion, and operational reliability. Task success measures the usable result produced by the complete provider path, not model intelligence in isolation.
Read the complete inference benchmark
Metric definitions, request scheduling, task rubrics, failure handling, and the complete provider scorecard live on the Inference Benchmark →