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Groq vs Together AI: Pricing and Ratings Compared (2026)

Entry prices and free plans as read on each vendor's pricing page, and user ratings as published on review sites, for Groq and Together AI side by side. This page compares data; it is not a hands-on review.

On the data: On the data below, Groq leads on a free plan. We do not name an overall winner for this pair.

Data comparison compiled by Toolradar, not hand-reviewed Methodology
Data comparison 6 user reviews compared Pricing checked Oct 7, 2026

Short on time? Here's the quick answer

Based on published vendor pricing and features and on public review data, here's who should pick what:

Groq

Ultra-fast LLM inference platform

Best for you if:

  • • You want a free tier before you commit

Together AI

Run open-source LLMs with serverless inference and fine-tuning

Best for you if:

  • • You want many open models
At a glance: Groq vs Together AI
At a Glance
Groq Groq
Together AI Together AI
Starts at
Free plan
Not published
Category
Cloud & Infrastructure GPU Cloud
Cloud & Infrastructure GPU Cloud
Rating
n/a 4.0/5 G2 4.0 6 reviews
Free plan
Yes No
Watch out for
Batch API discount requires minimum volume Minimum charges for specialized fine-tuning models

Choose Groq or Together AI?

Groq

Choose Groq if

  • You want a free tier before you commit
  • You want fastest inference speeds available, often 500-1000+ tokens per second on supported models
  • You want transparent per-token pricing with no monthly fees or minimum spend
Together AI

Choose Together AI if

  • You want many open models
  • You want competitive pricing

In-Depth Analysis

Groq Groq

Ultra-fast LLM inference platform

Good value

Groq's Free Tier is generous for experimentation, but the Pay-as-you-go pricing for Llama 3.1 8B at $0.05/M input tokens is competitive with other inference APIs, while Llama 4 Scout at $0.11/M is slightly above average for mid-size models.

Watch out

Batch API discount requires minimum volume

Strengths

  • Pro: Fastest inference speeds available, often 500-1000+ tokens per second on supported models
  • Pro: Transparent per-token pricing with no monthly fees or minimum spend
  • Pro: Drop-in replacement for OpenAI API with minimal integration effort
  • Pro: Wide model selection spanning LLMs, speech recognition, and text-to-speech
  • Pro: Prompt caching and batch API cut costs significantly for high-volume workloads

Weaknesses

  • Con: No proprietary frontier model, relies entirely on open-source model ecosystem
  • Con: Model selection is narrower than major cloud providers like AWS Bedrock or Azure AI
  • Con: Text-to-speech limited to a small number of languages and voices
  • Con: No built-in fine-tuning or model customization capabilities
  • Con: Enterprise on-premises pricing requires custom sales engagement with no public rates

Key features

Custom LPU inference chip delivering sub-second latency on large language models OpenAI-compatible API requiring minimal code changes to migrate existing applications Support for 10+ open-source LLMs including Llama 4, Qwen3, and GPT-OSS families Whisper-based automatic speech recognition at up to 228x real-time speed Text-to-speech generation via Canopy Labs Orpheus models in multiple languages Prompt caching with 50% input token discount for repeated context

Together AI Together AI

Run open-source LLMs with serverless inference and fine-tuning

Good value

The 50% discount on batch API is a strong value-add for high-volume users.

Watch out

Minimum charges for specialized fine-tuning models

Strengths

  • Pro: Many open models
  • Pro: Competitive pricing
  • Pro: Fast inference
  • Pro: Good for startups
  • Pro: Fine-tuning available

Weaknesses

  • Con: Smaller than big providers
  • Con: Model quality varies
  • Con: Support basic
  • Con: Documentation gaps
  • Con: Newer platform

Key features

LLM inference Image generation Fine-tuning GPU cloud Batch processing Code execution

Plans and prices: Groq vs Together AI

Plans and prices of Groq and Together AI, as read on each vendor's pricing page. Each plan keeps its own billing unit.
Tool Plans and prices Source
Groq
  • Free Tier: Free
  • Pay-as-you-go: Usage-based, one-time or minimum-commitment pricing
  • Enterprise: Custom pricing
groq.com/pricing read Sep 30, 2026
Together AI
  • Serverless Inference: Custom pricing
  • Fine-Tuning: Custom pricing
  • GPU Cloud: Custom pricing
together.ai/pricing read Oct 7, 2026

Prices as read on each vendor's own pricing page on the date shown. Plans are listed per tool and are not matched against the other tool's plans: a plan name or price in one column says nothing about the same row in the other. Details on Groq pricing and Together AI pricing.

Key Takeaways

Groq

  • Has a free plan

Together AI

  • Choose if you want run open-source LLMs with serverless inference and fine-tuning

What the data shows

On the data below, Groq leads on a free plan. We do not name an overall winner for this pair.

  • Only Together AI has a published user rating (4.0/5 from 6 reviews); Groq has none we can show.
  • Only Groq has a free plan.

Criteria: user rating (only above 20 reviews on both sides, gap of 0.2 or more), entry price (only on the same billing basis), free plan. How we rate

Frequently Asked Questions

How do Groq and Together AI compare in 2026?

On the data below, Groq leads on a free plan. We do not name an overall winner for this pair. Only Together AI has a published user rating (4.0/5 from 6 reviews); Groq has none we can show. Only Groq has a free plan.

What are Groq and Together AI used for?

Groq: Ultra-fast LLM inference platform. Together AI: Run open-source LLMs with serverless inference and fine-tuning.

What does Groq cost vs Together AI?

Groq has no public paid-plan price on file. Together AI has no public paid-plan price on file. Prices read on the vendors' pricing pages, latest check Oct 7, 2026.

What's the main difference between Groq and Together AI?

Groq's main strength: fastest inference speeds available, often 500-1000+ tokens per second on supported models. Together AI's main strength: many open models.

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