Baseten alternatives, benchmarked
What the benchmark found. Modal was the lowest-P99 measured alternative at 3.28 seconds, compared with 3.23 seconds for Baseten. Modal's task success rate was 99.3%.
What this page compares. Baseten is compared with every other provider that served the same GLM 5.3 Flash microtask workload. This is not a feature-directory list: each alternative received the same 600 questions under the same streaming, reasoning, sampling, timeout, and concurrency contract.
How to read the result. The table expresses every alternative as a delta from Baseten on E2E P99, task success, and slow-tail token generation speed. Positive and negative deltas retain their natural direction, so each column states whether lower or higher is better.
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 ↗
How measured Baseten alternatives differ from Baseten
The Baseten row is the baseline and is not repeated in the alternatives table. Compare the deltas before treating a faster provider as a substitute: an alternative can gain latency while losing successful-result yield.
| Alternative / API | E2E P99 | Δ P99 vs Baseten | Task success | Δ success | Generation P95 | Δ P95 |
|---|---|---|---|---|---|---|
| Modalzai-org/GLM-5.3-Flash ↗ | 3.28 s | +50 ms | 99.3% | +3.5 pp | 84.7 tok/s | +23.1 tok/s |
| Telnyxzai-org/GLM-5.3-Flash ↗ | 3.48 s | +250 ms | 99.5% | +3.7 pp | 67.5 tok/s | +5.9 tok/s |
| Novita AIzai-org/glm-5.3-flash ↗ | 7.25 s | +4020 ms | 94.2% | -1.7 pp | 29.6 tok/s | -32.1 tok/s |
| Z.AIglm-5.3-flash ↗ | 8.59 s | +5362 ms | 97.5% | +1.7 pp | 27.8 tok/s | -33.8 tok/s |
| Fireworks AIaccounts/fireworks/models/glm-5p3-flash ↗ | 10.5 s | +7259 ms | 99.5% | +3.7 pp | 27.9 tok/s | -33.8 tok/s |
| Parasailzai-org/GLM-5.3-Flash ↗ | 11.5 s | +8283 ms | 98.3% | +2.5 pp | 22.8 tok/s | -38.8 tok/s |
| Together AIzai-org/GLM-5.3-Flash ↗ | 12.4 s | +9221 ms | 98.5% | +2.7 pp | 34.0 tok/s | -27.6 tok/s |
| Nebiuszai-org/GLM-5.3-Flash ↗ | 15.0 s | +11742 ms | 84.8% | -11.0 pp | 78.8 tok/s | +17.2 tok/s |
| DeepInfrazai-org/GLM-5.3-Flash ↗ | 17.1 s | +13842 ms | 95.5% | -0.3 pp | 9.0 tok/s | -52.7 tok/s |
Workflows to test before replacing Baseten
- Real-time structured routing. Replay your shortest blocking JSON tasks and compare E2E P95/P99 with Baseten; this benchmark's ticket-triage family is the closest measured proxy.
- Contract and document extraction. Check exact task success before migrating. The benchmark requires complete typed contract objects, so it exposes substitutions that are fast but less dependable.
- Streamed assistant responses. Compare TTFA for the visible start and generation P95 for slow-tail continuation rather than choosing from median throughput alone.
Baseten alternatives — questions unique to this comparison
Which measured alternatives beat Baseten on E2E P99?
No measured alternative had a lower E2E P99 than Baseten's 3.23 seconds in this run.
How does Baseten's task success compare with lower-latency options?
No measured alternative improved both E2E P99 and task success relative to Baseten on this workload.
Can a Baseten-compatible chat-completions client use this ranking directly?
The measured alternatives expose OpenAI-compatible chat-completions surfaces, but authentication, base URLs, and model identifiers differ. Treat the ranking as a shortlist, then validate your Baseten client against the linked API documentation before migrating.
Read the complete inference benchmark
Metric definitions, request scheduling, task rubrics, failure handling, and the complete provider scorecard live on the Inference Benchmark →