Modal vs RouterPlus: Token Pricing, Speed & Intelligence
Full comparison of Modal and RouterPlus — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Modal
Managed inference API — 10 shared-endpoint models with per-token pricing
Modal Shared Endpoints serve a fixed catalog of models from Modal-managed pools. Modal manages the hardware and autoscaling, and usage is billed per token. Shared Endpoints have model-specific concurrency limits on concurrent in-flight requests. Prices are published rates from modal.com/docs/guide/supported-models.md, re-read 2026-10-31.
RouterPlus
API router / marketplace — 117 text models with per-route pricing
RouterPlus is an API router and marketplace offering access to 117+ text models. Prices shown are the published base catalog rates — actual price depends on the selected route and context, and is not a guaranteed bill. RouterPlus provides per-route pricing transparency with 27 models having numerically different route prices.
Key metric comparison
—
—
—
—
—
—
—
—
—
—
—
—
Live token pricing
Strengths and weaknesses
Modal
RouterPlus
Key differentiators
Modal Shared Endpoints provide managed per-token inference on a fixed 10-model catalog with published cached-input pricing and no infrastructure to manage.
An API router with 117 text models and per-route pricing transparency — the catalog rate is a published base rate, not a guaranteed bill; actual price depends on selected route and context.
Frequently asked questions
Modal FAQs
What models does Modal offer on Shared Endpoints?
Modal Shared Endpoints currently serve 10 models: GLM 5.3 Flash NVFP4, DeepSeek V4.1 Flash 1017, DeepSeek V4.1 Flash, GLM 5.3 Flash, Muse Spark Open, GLM 5.3, Inkling NVFP4, Qwen3.8-Max, Qwen3.8-Max VL, and Kimi K3. Use the model table above for per-model pricing and capability details. Source: Modal's published Shared Endpoints catalog, re-read 2026-10-31.
How much does Modal charge per 1M tokens?
Modal Shared Endpoints input prices range from $0.15/1M (GLM 5.3 Flash NVFP4) to $3.00/1M (Kimi K3). All models include cached-input pricing. See the model table for full per-model rates.
Does Modal offer prompt caching?
Yes. All 10 models in the Modal Shared Endpoints catalog have published cached-input pricing, ranging from $0.005/1M (DeepSeek V4.1 Flash 1017) to $0.30/1M (Kimi K3). Depending on the model, the cached-input rate is 77.5% to 98% below the standard input rate. Source: Modal's published Shared Endpoints rates, re-read 2026-10-31.
RouterPlus FAQs
Are RouterPlus prices guaranteed?
No. RouterPlus prices shown are published base catalog rates. Actual price depends on the selected route and context. 27 models have numerically different route prices. Check route details before production use.
What models does RouterPlus offer?
RouterPlus offers 117 text models including Claude 5 (Fable 5.1, Opus 5-5, Sonnet 5-5, Haiku 5-5), GPT-6 Astra, Gemini 3.x, Grok 4.x, Kimi K3, GLM-5.3, Qwen 3.8 Max, DeepSeek V4 Pro, Mistral Large 4, and many more. See the model table for current rates.
What is the RouterPlus API base URL?
The RouterPlus API base is https://api.routerplus.com/v1 with OpenAI-compatible endpoints. See https://app.routerplus.com/docs/models for full documentation.
Provider resources
Modal — Managed inference API — 10 shared-endpoint models with per-token pricing
Modal Shared Endpoints serve a fixed catalog of models from Modal-managed pools. Modal manages the hardware and autoscaling, and usage is billed per token. Shared Endpoints have model-specific concurrency limits on concurrent in-flight requests. Prices are published rates from modal.com/docs/guide/supported-models.md, re-read 2026-10-31.
Modal Shared Endpoints provide managed per-token inference on a fixed 10-model catalog with published cached-input pricing and no infrastructure to manage.
RouterPlus — API router / marketplace — 117 text models with per-route pricing
RouterPlus is an API router and marketplace offering access to 117+ text models. Prices shown are the published base catalog rates — actual price depends on the selected route and context, and is not a guaranteed bill. RouterPlus provides per-route pricing transparency with 27 models having numerically different route prices.
An API router with 117 text models and per-route pricing transparency — the catalog rate is a published base rate, not a guaranteed bill; actual price depends on selected route and context.
Key strengths compared
Modal
- Managed hardware and autoscaling — no infrastructure to operate
- Published per-token rates including cached-input pricing
- OpenAI-style per-token billing across all 10 models
- Small fixed catalog of 10 models
- Model-specific concurrency limits on shared pools
RouterPlus
- Wide catalog: 117 text models including Claude, GPT, Gemini, Grok, Kimi, GLM, Qwen, Mistral, and more
- Per-route pricing transparency — see actual route prices, not just a blended rate
- OpenAI-compatible API at api.routerplus.com/v1
- Catalog rate is not a guaranteed bill — actual price depends on selected route and context
- API router/marketplace — not a direct compute provider
Key weaknesses compared
Modal
- Small fixed catalog of 10 models
- Model-specific concurrency limits on shared pools
- Prices are published rates re-read 2026-10-31, not continuously collected
RouterPlus
- Catalog rate is not a guaranteed bill — actual price depends on selected route and context
- API router/marketplace — not a direct compute provider
- 27 models have numerically different route prices; check route details before production use
Provider category context
Modal is a inference api. RouterPlus is a inference api. Both are inference api providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both Modal and RouterPlus host open-weight models. The key differentiators are latency, throughput, and which specific model versions each provider offers. Check the speed metrics above — inference API providers often differ significantly on tokens-per-second for the same model. Pricing is typically competitive between them; availability of specific model versions (e.g., Llama 3.1 405B, DeepSeek V3) may be the deciding factor.