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Together AI vs Boundless
Together AI covers open-model serving, fine-tuning and GPU clusters. Boundless serves open models per token and has engineers tune reserved capacity for you.
By The Subconscious Team · Updated
Together AI vs Boundless: key differences
Together AI puts serverless, batch, provisioned throughput with a 99% SLA, dedicated deployments and GPU clusters on one bill, with 30+ open text models including GLM 5.3, DeepSeek V4.1 Flash and Kimi K3. Training covers LoRA and full SFT from $0.48 per million training tokens, with RL in beta, and reserved H100s start at $3.19 an hour. Boundless carries the same three models, with GLM-5.3 at $1.12 in and $3.52 out per million tokens, DeepSeek V4.1 Flash at $0.20 in and $1.00 out and Kimi K3 at $2.30 in and $11.40 out. It offers no fine-tuning. On its tailored tier, Boundless engineers tune precision, batching, caching and speculative decoding on reserved capacity.
Together is the pick for training or post-training on your own data and serving the result, or for renting clusters. Boundless fits teams that want someone else to run the serving stack against contracted uptime and latency targets. Together has no free tier, while Boundless gives free credits to start and a free two-week evaluation on real traffic.
What Together AI and Boundless 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 GLM 5.3, DeepSeek V4.1 Flash, DeepSeek V4 Pro 0813, Kimi K3, 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, GLM 5.3, DeepSeek V4.1 Flash
Full Together AI profileBoundless
Boundless launched in September 2026 as an inference partner for AI-native startups. It sells two things. The Model API serves pre-tuned models on shared capacity, billed per token from prepaid credits with a budget per API key. Tailored inference reserves capacity for one customer, and Boundless engineers pick the model on the customer’s own evals, tune precision, batching, caching, speculative decoding and parallelism, then run the deployment against uptime, throughput and latency targets written into the contract. A free two-week evaluation tests those targets on real traffic against the customer’s current provider first.
Example models: GLM-5.3, DeepSeek V4.1 Flash, Kimi K3
Full Boundless profileShould you choose Together AI or Boundless?
Together AI
Choose Together AI for
- Fine-tuning and RL on your data
- Reserved GPU clusters
- A broad open-model catalog
Boundless
Choose Boundless for
- Managed tuning of the serving stack
- Free credits and a two-week trial
- Contracted latency targets
Together AI vs Boundless at a glance
| Attribute | Together AI | Boundless |
|---|---|---|
| Model access | Open weights | Open weights, plus closed GPT and Claude |
| Flagship models | Kimi K3, GLM 5.3, DeepSeek V4.1 Flash, Qwen 3.8 | GLM-5.3, DeepSeek V4.1 Flash, Kimi K3 |
| Speed | 0.99s TTFT on DeepSeek V4 Pro | 342 tok/s on DeepSeek V4.1 Flash 1017 (Vercel) |
| Price | Parity with Fireworks and Baseten | $0.04–$2.30 in, $0.21–$11.40 out per 1M (open) |
| Customization | LoRA and full SFT; RL in beta | Serving-stack tuning, no fine-tuning |
| Deployment | Serverless, dedicated, GPU clusters | Serverless API, reserved tailored capacity |
| Long context | 512K on DeepSeek V4 Pro 0813 | 1M context on most models |
Frequently asked questions
What is the difference between Together AI and Boundless?
Together AI covers open-model serving, fine-tuning and GPU clusters. Boundless serves open models per token and has engineers tune reserved capacity for you.
When should I choose Together AI over Boundless?
Fine-tuning and RL on your data; Reserved GPU clusters; A broad open-model catalog.
When should I choose Boundless over Together AI?
Managed tuning of the serving stack; Free credits and a two-week trial; Contracted latency targets.
Is Together AI or Boundless cheaper?
Together AI: Parity with Fireworks and Baseten. Boundless: $0.04–$2.30 in, $0.21–$11.40 out per 1M (open). The cheaper choice depends on the model and workload.
Which has more context, Together AI or Boundless?
Together AI: 512K on DeepSeek V4 Pro 0813. Boundless: 1M context on most models.
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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.