Cohere vs Modal: Token Pricing, Speed & Intelligence
Full comparison of Cohere and Modal — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Cohere
Command A and Command R7B — enterprise RAG, North platform, and on-premise deployment
Cohere focuses on enterprise NLP, particularly retrieval-augmented generation (RAG) and search. Command A is their 2025 flagship — a 111B-parameter model optimised for agentic and multi-step enterprise workflows. Command R7B is the efficient tier. The North platform provides a managed enterprise AI environment with private deployment, compliance controls, and a complete RAG stack (LLM + Embed 4 + Rerank 3). Check cohere.com/pricing for current rates.
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.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Cohere
Modal
Key differentiators
The only major LLM provider with a complete enterprise RAG stack — Command A, Embed 4, and Rerank 3 — plus the North platform for private deployment and compliance-grade enterprise AI.
Modal Shared Endpoints provide managed per-token inference on a fixed 10-model catalog with published cached-input pricing and no infrastructure to manage.
Frequently asked questions
Cohere FAQs
What is Command A?
Command A is Cohere's 2025 flagship model — a 111-billion-parameter model optimised for agentic and multi-step enterprise workflows, with a 256K token context window and strong tool-use performance. Check cohere.com/pricing for current rates.
What is Command R7B?
Command R7B is Cohere's efficient-tier model designed for high-volume RAG and classification workloads where cost efficiency is the priority. Check cohere.com/pricing for current rates.
What is the Cohere North platform?
North is Cohere's managed enterprise AI platform, providing a complete environment for building, deploying, and managing AI applications with private deployment, compliance controls, and integrated RAG capabilities. It is designed for enterprises with strict data residency requirements.
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.
Provider resources
Cohere — Command A and Command R7B — enterprise RAG, North platform, and on-premise deployment
Cohere focuses on enterprise NLP, particularly retrieval-augmented generation (RAG) and search. Command A is their 2025 flagship — a 111B-parameter model optimised for agentic and multi-step enterprise workflows. Command R7B is the efficient tier. The North platform provides a managed enterprise AI environment with private deployment, compliance controls, and a complete RAG stack (LLM + Embed 4 + Rerank 3). Check cohere.com/pricing for current rates.
The only major LLM provider with a complete enterprise RAG stack — Command A, Embed 4, and Rerank 3 — plus the North platform for private deployment and compliance-grade enterprise AI.
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.
Key strengths compared
Cohere
- Command A: 111B model optimised for agentic enterprise workflows
- Command R7B: efficient tier — cost-effective for high-volume RAG and classification
- Embed 4 + Rerank 3: strong RAG stack with native grounding and citations
- Intelligence scores trail OpenAI and Anthropic at frontier tier
- Less suitable for creative or general chat tasks
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
Key weaknesses compared
Cohere
- Intelligence scores trail OpenAI and Anthropic at frontier tier
- Less suitable for creative or general chat tasks
- Smaller developer community than OpenAI/Anthropic
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
Provider category context
Cohere is a frontier lab, founded in 2019. Modal is a inference api. Cohere as a frontier lab trains and serves its own proprietary models. Modal as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers but without access to proprietary frontier models.
How to choose between them
Choose Cohere if you need command a: 111b model optimised for agentic enterprise workflows. Choose Modal if you need managed hardware and autoscaling — no infrastructure to operate. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.