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Self-hosted production inference fleet

Always-on model serving on rented GPUs with control over stacks.

GET /api/decide?jtbd=production-inference-fleetAPI embedRunPod vs CoreWeaveRunPod vs Modal

At a glance — Oct 2026

Updated 2026-10-27 · forward this page: /jtbds/production-inference-fleet#brief

Scores as of 2026-10-19 (8 days old).

Depot Pick
RunPod · 8.32/10 for this job (curated estimate, high confidence)

reliability + dx + pricePerf balance.

Runner-up
CoreWeave · 7.71/10

Scores higher than the pick on: Capability fit, Latency / reliability, Privacy / data retention, Maturity / track record.

When not to use the pick
Prefer tokens not GPUs — Fireworks/Together. Huge enterprise K8s — CoreWeave/AWS.
Lock-in / migration
The pick has lower stored lock-in risk than runner-up CoreWeave (3.5 vs 6.5). Self-host fallback listed for this job: vLLM.
Sourced price (no comparable unit)

Pick: no sourced price in this job's unit (no_matching_sourced_price).

No cheapest SKU (no_comparable_unit_for_job). No price was invented.

Free option
  • vLLM (oss) — source, as of 2026-10-25
Failure modes to watch
  • Runaway spend: Set a budget and a tool-call cap per task. Alert when spend jumps. Stop the run at the cap instead of summarizing a partial trace as success.
Reported outcomes (submitted reports only)

This job: loading… JSON · reports never change scores · seed/test records excluded

Depot Pick (RunPod) on this job: loading… JSON · reports never change scores · seed/test records excluded

Cite: Agent Provider Depot, Depot Pick for production-inference-fleet: runpod, scores as of 2026-10-19. Agents: GET /api/decide?jtbd=production-inference-fleet

Free Self-hosted production inference fleet options

Depot Pick

RunPod

reliability + dx + pricePerf balance.

Pricing (directional): Secure Cloud + Community Cloud; serverless per-second; H100 often ~$2–3+/hr depending tier; spot cheaper.

Cite: Depot Pick for production-inference-fleet: runpod
Overall
8.3
curated_estimate
confidence: high · as of 2026-10-19
Capability fit
8.8
Price / performance
9.0
Latency / reliability
8.0
Developer & agent DX
8.8
Privacy / data retention
7.0
Lock-in risk (higher = worse)
3.5
Maturity / track record
8.2

Lock-in risk: higher = more lock-in (worse). Overall already inverts this dimension.

Sources: RunPod: https://www.runpod.io · GPU cloud comparisons: https://www.runpod.io/articles/alternatives/best-gpu-cloud-providers-for-ai-and-ml

Depot default for self-serve GPUs. Secure Cloud for anything customer-facing; Community/spot for batch.

Quote for Self-hosted production inference fleet

Depot Pick stays RunPod. Prices below are sourced SKU rows only (as of 2026-10-27). Input and output are not blended. GET /api/quote?jtbd=production-inference-fleet

Nothing was compared. no comparable sourced unit for this job; chat input $/1M and other units were not borrowed pickIsPriceWinner is null.

  • A100 SXM Pod (Community Cloud) usd_per_gpu_hour $1.39 source as of 2026-10-19
  • A100 SXM Pod (Secure Cloud) usd_per_gpu_hour $1.79 source as of 2026-10-19
  • B200 Pod (Community Cloud) usd_per_gpu_hour $5.98 source as of 2026-10-19
  • B200 Pod (Secure Cloud) usd_per_gpu_hour $7.99 source as of 2026-10-19
  • H100 SXM Pod (Community Cloud) usd_per_gpu_hour $2.69 source as of 2026-10-19
  • H100 SXM Pod (Secure Cloud) usd_per_gpu_hour $3.99 source as of 2026-10-19
  • H200 Pod (Community Cloud) usd_per_gpu_hour $3.59 source as of 2026-10-19
  • H200 Pod (Secure Cloud) usd_per_gpu_hour $5.29 source as of 2026-10-19
  • L40S Pod (Community Cloud) usd_per_gpu_hour $0.79 source as of 2026-10-19
  • L40S Pod (Secure Cloud) usd_per_gpu_hour $1.09 source as of 2026-10-19
  • RTX 4090 Pod (Community Cloud) usd_per_gpu_hour $0.34 source as of 2026-10-19
  • RTX 4090 Pod (Secure Cloud) usd_per_gpu_hour $0.89 source as of 2026-10-19

3 of 8 candidates have no sourced price row. 8 are excluded from the Matching price comparison (none). no comparable sourced unit for this job; chat input $/1M and other units were not borrowed

Runners-up

CoreWeave

Enterprise training/inference fleet pick. Skip if you just need a single H100 for an afternoon — use RunPod.

7.7
gpukubernetesenterprisetraining

Modal

Depot darling for Python agent backends and bursty GPU jobs. If you think in functions not VMs, start here.

8.4
serverlessgpupythonsandbox

Baseten

Strong custom-model serving alternative to Replicate/Modal when you bring your own model.

8.0
inferenceservingtrussgpu

AWS GPU (EC2/P5/SageMaker)

Use when AWS is destiny. For greenfield agent GPUs, neoclouds win on price and speed-to-pod.

7.7
gpuawsenterprisesagemaker

FriendliAI

Open-model production peer when latency/tool-calling matter. Fireworks remains depot open-model default…

8.0
inferenceopen-weightsdedicated-gpulow-latency

When NOT to use the top pick

Prefer tokens not GPUs — Fireworks/Together. Huge enterprise K8s — CoreWeave/AWS.

Full ranking (score table)

Ranked with this JTBD's weights. Scores are curated estimates unless marked otherwise. Agents: prefer /api/decide then this table for tie-breaks.

#ProviderOverallFit$/perfLatencyDXAs of
1Modal8.49.08.28.69.62026-10-19
2RunPodDepot Pick8.38.89.08.08.82026-10-19
3FriendliAI8.08.48.08.48.22026-10-01
4Baseten8.08.47.88.48.62026-09-14
5AWS GPU (EC2/P5/SageMaker)7.79.44.89.57.02026-09-14
6CoreWeave7.79.25.59.07.52026-10-19
7NVIDIA NIM / NGC7.78.67.08.06.82026-10-19
8Anyscale7.58.26.58.07.52026-09-14

Score methodology for this job

reliability + dx + pricePerf balance.

  • capabilityFit: 25%
  • pricePerformance: 18%
  • latencyReliability: 15%
  • developerDx: 15%
  • privacyPosture: 10%
  • lockInRisk: 7%
  • maturity: 10%