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Together AI vs Cerebras
Cerebras posts the fastest public tokens per second on a two-model shared catalog. Together gives up that peak for dozens of open models, fine-tuning and GPU clusters.
By The Subconscious Team · Updated
Together AI vs Cerebras: key differences
Cerebras runs models on a wafer-scale chip and lists GPT-OSS 120B near 3,000 tokens per second at $0.35 in and $0.75 out. That speed comes with a thin shared catalog, just GPT-OSS 120B and Gemma 4 31B as of August 2026, with other families behind dedicated endpoints and sales conversations. Together is the opposite shape: a broad self-serve list across text, image, video, speech and embeddings, plus batch, provisioned throughput and raw H100 clusters from $3.19 an hour. Together also offers LoRA, full SFT and an RL beta, which Cerebras does not advertise.
The speed gap matters only when generation is the wait. Cerebras itself notes that an agent mostly waiting on tools or hidden reasoning gains little. For voice, live autocomplete and streaming UIs on GPT-OSS, Cerebras is hard to beat. For everything else, including model choice, custom training and cost control through batch, Together covers more. Some teams run both: Together as the default host, Cerebras for the one latency-critical path.
What Together AI and Cerebras 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 profileCerebras
Cerebras builds a single chip the size of a silicon wafer, and its inference cloud is the fastest public host on the models it serves. Its developer table lists GPT-OSS 120B near 3,000 tokens per second, about six times Groq on the same weights, at $0.35 in and $0.75 out per million. The public shared catalog is thin, just GPT-OSS 120B and Gemma 4 31B as of August 2026. More model families live on dedicated endpoints and through partners like OpenRouter, Hugging Face, Vercel and AWS Marketplace.
Example models: GPT-OSS 120B, Gemma 4 31B
Full Cerebras profileShould you choose Together AI or Cerebras?
Together AI
Choose Together AI for
- Self-serve access to many open model families
- Fine-tuning and serving a custom checkpoint
- Batch jobs at up to 50% off
Cerebras
Choose Cerebras for
- Streaming UIs where output speed is the bottleneck
- Long-output agent steps on GPT-OSS 120B
- OpenAI's Ultrafast GPT-5.6 Sol preview on wafer-scale hardware
Together AI vs Cerebras at a glance
| Attribute | Together AI | Cerebras |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | Kimi K3, DeepSeek V4, GLM 5.2, Qwen 3.8 | GPT-OSS 120B, Gemma 4 31B |
| Speed | 0.99s TTFT on DeepSeek V4 Pro | ~3,000 tok/s on GPT-OSS 120B |
| Price | Parity with Fireworks and Baseten | $0.35 in, $0.75 out (GPT-OSS 120B) |
| Customization | LoRA and full SFT; RL in beta | Unknown |
| Deployment | Serverless, dedicated, GPU clusters | Shared API, dedicated, partners |
| Long context | 512K on DeepSeek V4 Pro | Unknown |
Frequently asked questions
What is the difference between Together AI and Cerebras?
Cerebras posts the fastest public tokens per second on a two-model shared catalog. Together gives up that peak for dozens of open models, fine-tuning and GPU clusters.
When should I choose Together AI over Cerebras?
Self-serve access to many open model families; Fine-tuning and serving a custom checkpoint; Batch jobs at up to 50% off.
When should I choose Cerebras over Together AI?
Streaming UIs where output speed is the bottleneck; Long-output agent steps on GPT-OSS 120B; OpenAI's Ultrafast GPT-5.6 Sol preview on wafer-scale hardware.
Is Together AI or Cerebras cheaper?
Together AI: Parity with Fireworks and Baseten. Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). The cheaper choice depends on the model and workload.
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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.