Modal vs Together AI

Side-by-side comparison of features, pricing, and ratings

Analysis generated Live tool data as of 2026-11-08
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Modal or Together AI: which should you choose?

DimensionModalTogether AI
PricingFree · from $250/moFree · from $0.0017/image
Best forPython teams with spiky or unpredictable GPU demand that should scale to zero, Startups shipping LLM inference without a reserved capacity planEngineering teams running open-weight models in production on per-token pricing, AI startups graduating from serverless trials to provisioned capacity with an SLA
Standout featuresServerless autoscaling from zero to thousands of GPUs with no capacity planning · Python SDK declaring function logic and hardware in one file · Per-second billing by GPU, CPU core, memory, and volume — no idle costServerless Inference APIs across a broad open-weight catalog · Chat, vision, image, audio, video, transcribe, embeddings, rerank and moderation endpoints · Batch Inference scaling to 30 billion tokens per model
Viability score97/10088/100
APIYesYes

Modal is the stronger pick for python teams with spiky or unpredictable gpu demand that should scale to zero; Together AI fits better for engineering teams running open-weight models in production on per-token pricing.

Built from live tool data, last verified 2026-11-08.

Modal
Modal

Modal's serverless GPU cloud runs Python functions and sandboxes with per-second billing, spinning up GPU inference and agent compute from

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Together AI
Together AI

Together AI is an AI cloud for open-weight models: per-token inference APIs with GPU clusters underneath.

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Pricing
Freemium
Freemium
Plans
StarterFree
Team$250/mo
EnterpriseCustom
Serverless Inference (per 1M tokens)Free
Image Generation (per image)From $0.0017/image
Batch Inference (per 1M tokens)Batch rates
Provisioned ThroughputCustom
Dedicated Model InferenceCustom
Dedicated Container InferenceCustom
GPU ClustersCustom
Popularity
4.6k views
3.6k views
Skill Level
Advanced
Advanced
API Available
Platforms
WebAPICLI
WebAPI
Categories
🖥️ GPU Cloud & Model Inference⚙️ Developer Infrastructure
🖥️ GPU Cloud & Model Inference
FeaturesModalTogether AI
Serverless autoscaling from zero to thousands of GPUs with no capacity planning
Python SDK declaring function logic and hardware in one file
Per-second billing by GPU, CPU core, memory, and volume — no idle cost
Published GPU rates from $0.000164/sec T4 to $0.001972/sec B300
Custom container runtime for sub-second starts on large images
LLM inference across B300, B200, H200 SXM, H100 SXM5, RTX PRO 6000, A100, L40S, A10, L4, T4
OpenAI-compatible endpoints under the modal | Access open intelligence banner
Dedicated Endpoints serving Reflection Beam (501B total, 23B active, 1M-token context)
Shared Endpoints with per-token billing for DeepSeek V4.1 Flash 1017 and Muse Spark Open
Programmatic Sandboxes scaling to 1M concurrent isolated Linux environments
Exit Snapshots (beta) capturing filesystem state on graceful and ungraceful exits
Fine-tuning with SFT, LoRA, and full fine-tunes on single or multi-GPU
Elastic single- or multi-node training with frameworks like slime and Miles
Multi-modal inference for image, video, audio, and embeddings
Batch and async inference for evals, embeddings, and dataset generation
Serverless Inference APIs across a broad open-weight catalog
Chat, vision, image, audio, video, transcribe, embeddings, rerank and moderation endpoints
Batch Inference scaling to 30 billion tokens per model
Cached-input rates published per model, e.g. $0.006 per 1M on DeepSeek V4.1 Flash
Per-image pricing for SD XL, FLUX, GPT Image 2 and Nano Banana Pro
Provisioned Throughput with reserved token capacity and a 99% uptime SLA
Drop-in API compatibility from serverless to dedicated deployments
Dedicated Model Inference on hardware you control
Dedicated Container Inference for video, audio and image models
GPU Clusters with GB300, GB200, B300, B200, H200 and H100
On-demand NVIDIA B200 GPUs on Together GPU Clusters
Together Link: run open models inside your existing agent harness
Together Post-Training with custom RL and SFT loops
Managed Fine-Tuning (SFT and DPO) plus Evaluations
Sandbox for secure code environments and Managed Storage with zero egress fees
IntegrationsModalTogether AI
Slack
Hugging Face
Gradio
AWS Marketplace
GCP Marketplace
Datadog
Okta
CodeSandbox
Weights & Biases
LangChain
LlamaIndex

Frequently Asked Questions

Which is better, Modal or Together AI?

The best choice between Modal and Together AI depends on your specific use case — we compare them independently on features, current pricing, integrations, and real-world signals (with an on-demand sentiment scan available for each). See the side-by-side breakdown above to match them to your needs.

What are the main differences between Modal and Together AI?

The key differences include pricing model, feature set, platform support, and skill level requirements. Review the full comparison on RightAIChoice for a detailed breakdown.

Is there a free version of Modal or Together AI?

Check the pricing section in the comparison for the latest pricing details on both tools, including free tiers, trial options, and paid plans.

What else are Modal and Together AI compared with?

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Groq vs Together AI comparison

If you need real-time responsiveness under 200ms — chatbots, voice assistants, agentic systems — Groq's LPU is the clear winner, with day-zero model access and a dead-simple switch from OpenAI. But if

Where can you read more about Modal and Together AI?

Modal
View Modal reviewModal alternatives
Together AI
View Together AI reviewTogether AI alternatives

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Analysis generated by our model pipeline from live data: