Best inference provider for synchronous workflows with an SLA
What the benchmark found. Baseten recorded the lowest E2E P99 at 3.23 seconds on this run, with E2E P50 of 331 ms, task success of 95.8%, and failure rate of 0.0%. This evidence covers concurrency-one short calls; it does not model queue growth or saturation under production traffic.
What this page compares. A synchronous workflow cannot advance until inference returns a complete usable result. This page orders providers by complete-response tail latency and keeps the full submitted-request failure denominator beside it, matching the concerns of an API endpoint with a hard response-time SLA.
How to read the result. Allocate your inference budget using E2E P95 or P99 according to the SLA percentile you promise. The benchmark enforces a 20-second client timeout. Calls that time out or fail do not enter completion percentiles, so failure rate must be an explicit second gate.
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.
APIs used. The runner called each provider's OpenAI-compatible chat-completions surface. Baseten, Modal, Telnyx, Novita AI, Z.AI, Fireworks AI, Parasail, Together AI, Nebius, and DeepInfra used the model identifiers below; the links open the provider documentation used to verify each adapter.
- Baseten:
zai-org/GLM-5.3-Flash· API docs ↗ - Modal:
zai-org/GLM-5.3-Flash· API docs ↗ - Telnyx:
zai-org/GLM-5.3-Flash· API docs ↗ - Novita AI:
zai-org/glm-5.3-flash· API docs ↗ - Z.AI:
glm-5.3-flash· API docs ↗ - Fireworks AI:
accounts/fireworks/models/glm-5p3-flash· API docs ↗ - Parasail:
zai-org/GLM-5.3-Flash· API docs ↗ - Together AI:
zai-org/GLM-5.3-Flash· API docs ↗ - Nebius:
zai-org/GLM-5.3-Flash· API docs ↗ - DeepInfra:
zai-org/GLM-5.3-Flash· API docs ↗
Providers sorted for blocking inference SLAs
E2E P50, P95, and P99 show the complete-answer distribution; delta versus the lowest P99 quantifies tail budget consumed relative to the run leader. Task success and failures prevent incomplete calls from disappearing behind latency-only reporting.
| Provider | E2E P50 | E2E P95 | E2E P99 | Δ vs fastest P99 | Task success | Failure rate |
|---|---|---|---|---|---|---|
| Basetenzai-org/GLM-5.3-Flash ↗ | 331 ms | 2.29 s | 3.23 s | 0 ms | 95.8% | 0.0% |
| Modalzai-org/GLM-5.3-Flash ↗ | 574 ms | 1.90 s | 3.28 s | +50 ms | 99.3% | 0.0% |
| Telnyxzai-org/GLM-5.3-Flash ↗ | 669 ms | 2.33 s | 3.48 s | +250 ms | 99.5% | 0.0% |
| Novita AIzai-org/glm-5.3-flash ↗ | 1.74 s | 5.00 s | 7.25 s | +4020 ms | 94.2% | 4.0% |
| Z.AIglm-5.3-flash ↗ | 1.75 s | 4.83 s | 8.59 s | +5362 ms | 97.5% | 0.2% |
| Fireworks AIaccounts/fireworks/models/glm-5p3-flash ↗ | 1.95 s | 6.72 s | 10.5 s | +7259 ms | 99.5% | 0.0% |
| Parasailzai-org/GLM-5.3-Flash ↗ | 1.59 s | 7.74 s | 11.5 s | +8283 ms | 98.3% | 1.3% |
| Together AIzai-org/GLM-5.3-Flash ↗ | 609 ms | 3.66 s | 12.4 s | +9221 ms | 98.5% | 1.0% |
| Nebiuszai-org/GLM-5.3-Flash ↗ | 1.45 s | 7.45 s | 15.0 s | +11742 ms | 84.8% | 14.8% |
| DeepInfrazai-org/GLM-5.3-Flash ↗ | 1.83 s | 11.0 s | 17.1 s | +13842 ms | 95.5% | 4.0% |
Synchronous paths where the full response is the boundary
- Request-time enrichment. A web request waits for a typed model result before rendering or committing a transaction.
- Policy and routing checks. The application cannot choose a branch until classification JSON is complete and schema-valid.
- Chained API orchestration. Each blocking inference call consumes part of a larger end-to-end SLA and can compound tail delay.
Inference SLAs for blocking application paths
Which provider consumed the least P99 budget in a synchronous call?
Baseten recorded the lowest E2E P99 at 3.23 seconds on this run, with E2E P50 of 331 ms, task success of 95.8%, and failure rate of 0.0%. This evidence covers concurrency-one short calls; it does not model queue growth or saturation under production traffic.
Should a blocking inference SLA use E2E P95 or P99?
Use E2E P95 when the SLA promises that 95% of completed calls finish within a budget; use P99 for a stricter slow-tail commitment. In either case, specify a separate maximum failure rate because unsuccessful calls have no complete-answer latency sample.
How does the benchmark's 20-second timeout appear in SLA results?
The client stops a provider call at 20 seconds and records it as a timeout failure. That request is excluded from completion-latency percentiles but remains in the submitted denominator for timeout rate, failure rate, and task success.
Read the complete inference benchmark
Metric definitions, request scheduling, task rubrics, failure handling, and the complete provider scorecard live on the Inference Benchmark →




