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Together AI vs Groq
Groq trades catalog size for raw speed on its LPU chip. Together trades peak speed for the widest open-model menu, fine-tuning and GPU clusters.
By The Subconscious Team · Updated
Together AI vs Groq: key differences
This is a chip company against a platform company. Groq serves a small set of models, mostly GPT-OSS and Qwen 3.6, on its own LPU and publishes 500 to 1,000 tokens per second with tight tail latency. Together runs GPUs and covers far more ground: thirty-plus text models including Kimi K3 and DeepSeek V4, media models, embeddings, fine-tuning and raw clusters. Groq's context tops out around 131K and it does not host fine-tuned models, so any custom checkpoint rules it out. Groq's per-token prices on small models sit near the market floor, with cache and Batch discounts that stack.
There is also a question of trajectory. Groq's catalog is shrinking, with Llama 3.3 70B and Llama 3.1 8B shut down in August 2026, and its core engineers moved to NVIDIA under a licensing deal. Together keeps adding models within days of release. The workable split: Groq for voice agents and tight agent loops on GPT-OSS where every millisecond counts, Together for long contexts, frontier-scale open models and anything you plan to fine-tune.
What Together AI and Groq do
Together AI
Together AI is the broadest open-model platform in the category. One bill covers per-token serverless inference, batch at up to 50% off, provisioned throughput with a 99% SLA, dedicated deployments, raw GPU clusters, managed fine-tuning and code sandboxes for agents. The text catalog runs past thirty open models, including DeepSeek V4, Kimi K3, GLM 5.2, Qwen 3.8 and MiniMax M3, plus image, video, speech and embedding models. Token prices sit at parity with Fireworks and Baseten.
Example models: Kimi K3, DeepSeek V4 Pro
Full Together AI profileGroq
Groq serves open models on its own chip, the LPU, which keeps model weights in on-chip SRAM and runs a deterministic schedule instead of waiting on GPU memory. Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B. Latency stays tight between median and tail, which matters for strict SLAs. The API is OpenAI-compatible and also hosts Whisper for speech to text plus an agentic system called Groq Compound with built-in search and code execution.
Example models: GPT-OSS 120B, Qwen 3.6 27B
Full Groq profileShould you choose Together AI or Groq?
Together AI
Choose Together AI for
- Serving your own fine-tuned checkpoint
- Contexts beyond Groq's roughly 131K cap
- Large open models like Kimi K3 or DeepSeek V4
Groq
Choose Groq for
- Voice agents that cannot tolerate pauses
- Strict SLAs that depend on predictable tail latency
- Cheap, fast calls on GPT-OSS 20B or 120B
Together AI vs Groq at a glance
| Attribute | Together AI | Groq |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | Kimi K3, DeepSeek V4, GLM 5.2, Qwen 3.8 | GPT-OSS 120B, Qwen 3.6 27B |
| Speed | 0.99s TTFT on DeepSeek V4 Pro | 500–1,000 tok/s |
| Price | Parity with Fireworks and Baseten | Near the floor on small models |
| Customization | LoRA and full SFT; RL in beta | No fine-tuned model hosting |
| Deployment | Serverless, dedicated, GPU clusters | GroqCloud API |
| Long context | 512K on DeepSeek V4 Pro | Around 131K max |
Frequently asked questions
What is the difference between Together AI and Groq?
Groq trades catalog size for raw speed on its LPU chip. Together trades peak speed for the widest open-model menu, fine-tuning and GPU clusters.
When should I choose Together AI over Groq?
Serving your own fine-tuned checkpoint; Contexts beyond Groq's roughly 131K cap; Large open models like Kimi K3 or DeepSeek V4.
When should I choose Groq over Together AI?
Voice agents that cannot tolerate pauses; Strict SLAs that depend on predictable tail latency; Cheap, fast calls on GPT-OSS 20B or 120B.
Is Together AI or Groq cheaper?
Together AI: Parity with Fireworks and Baseten. Groq: Near the floor on small models. The cheaper choice depends on the model and workload.
Which has more context, Together AI or Groq?
Together AI: 512K on DeepSeek V4 Pro. Groq: Around 131K max.
Related comparisons
Running long-horizon agents?
If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.