ML Platforms
Groq vs Together AI.
Both sit in ML Platforms, scored on the same six pillars from the same published methodology. Here is where they actually differ.
The short answer
Groq scores higher — 85.0 against 80.6, a margin of 4.4 points. That is the overall answer, not the whole one: the pillar breakdown below is where the decision usually actually gets made.
Groq leads on value for money, maturity & reliability and integrations & ecosystem.
Groq
85.0
Excellent
Ultra-fast LLM inference on custom LPU hardware.
- From
- Free tier / pay per token
- Pricing
- Usage-based
- Maturity
- Established
- Founded
- 2016
Together AI
80.6
Strong
Fast inference and fine-tuning for open-source models.
- From
- Pay-as-you-go per token / per GPU-hour
- Pricing
- Usage-based
- Maturity
- Established
- Founded
- 2022
Pillar by pillar
The same six pillars and fixed weights used for every tool on the site. A lead of fewer than 5 points is not called for either side — these are evidence-backed judgements, not measurements. Read the methodology.
Capability
Level
Value for Money
Groq by 8
Security & Compliance
Level
Integrations & Ecosystem
Groq by 6
Maturity & Reliability
Groq by 8
Momentum
Level
Which one, and when
Pick Groq if
- →cost per unit of output is the binding constraint — it leads Value for Money by 8 points.
- →it has to hold up in production from day one — it leads Maturity & Reliability by 8 points.
- →it has to fit the stack you already run — it leads Integrations & Ecosystem by 6 points.
- →Latency-sensitive AI apps
- →Cost-efficient high-volume inference
- →Real-time agents and voice
The catch
- Open-weight models only, no frontier closed models
- Model catalog is curated and limited
Pick Together AI if
- →Shipping open models to production
- →Fine-tuning at lower cost
- →Teams avoiding vendor lock-in
The catch
- You own more of the model-selection and eval work than with a closed API
- Enterprise compliance surface still maturing vs hyperscalers
What each is good at
Groq
- ✓Fastest mainstream inference (hundreds of tok/s)
- ✓Very low cost per token
- ✓Drop-in OpenAI API compatibility
Together AI
- ✓Fast, cost-effective inference for a huge range of open models
- ✓OpenAI-compatible API makes switching low-friction
- ✓Fine-tuning and dedicated GPU capacity in one place
Other comparisons in ML Platforms
Comparing something else? Build your own side-by-side across any tools in the catalog.