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Together AI vs Hugging Face Inference Providers

Together is one of the hosts Hugging Face routes to. Going direct adds fine-tuning, dedicated capacity and GPU clusters; the router adds choice and failover.

By The Subconscious Team · Updated

Together AI vs Hugging Face Inference Providers: key differences

Together AI is on Hugging Face's partner list, so part of this comparison is direct versus routed. Through Hugging Face, a request for a model Together serves bills at Together's rate with no markup, and it can land on Together or on any of 16 other hosts depending on routing. Default routing picks the highest-throughput provider, :cheapest picks the lowest output price, and :together pins it. Going direct gets the full platform: 30+ open text models including DeepSeek V4, Kimi K3, GLM 5.2 and Qwen 3.8, batch at up to 50% off, provisioned throughput with a 99% SLA and dedicated deployments. Together serves DeepSeek V4 Pro with 512K context and a 0.99s time to first token. It has no free tier, while Hugging Face gives free accounts $0.10 a month in credits.

Together wins everything past plain inference. It runs LoRA and full-parameter SFT from $0.48 per million training tokens, reinforcement learning in closed beta with checkpoints that deploy straight to inference, and H100 clusters from $3.19 an hour reserved. Its July 2026 update added canary rollouts, shadow traffic and autoscaling on time to first token. Dedicated inference does cost noticeably more per GPU hour than a raw cluster on the same silicon. Hugging Face offers no fine-tuning and adds a network hop plus its own rate limits. Its value is not being tied to one host. The router lists 132 chat models, fails over automatically and shows live per-provider price and throughput, so a team can check whether Together is the right home for a model before signing up.

What Together AI and Hugging Face Inference Providers 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 profile

Hugging Face Inference Providers

Inference Providers is a router run by Hugging Face that sits in front of partner inference clouds. The current partner list covers Baseten, Cerebras, Cohere, DeepInfra, fal, Featherless AI, Fireworks, Groq, Novita, Nscale, OVHcloud, Public AI, Replicate, Scaleway, Together, WaveSpeedAI and Z.ai, plus Hugging Face's own HF Inference, which now mostly serves CPU workloads like embeddings and classification. Chat traffic goes through an OpenAI-compatible endpoint at router.huggingface.co/v1, and the Python and JavaScript clients add text-to-image, video, speech and embeddings. The router lists 132 chat models today, from GLM 5.3 and Kimi K3 to gpt-oss-120b on eleven providers.

Example models: GLM 5.3, Kimi K3, gpt-oss-120b

Full Hugging Face Inference Providers profile

Should you choose Together AI or Hugging Face Inference Providers?

Together AI

Choose Together AI for

  • Fine-tuning or RL, then serving the checkpoint
  • Dedicated capacity with a 99% SLA
  • Reserved H100 clusters for training runs

Hugging Face Inference Providers

Choose Hugging Face Inference Providers for

  • Checking Together against other hosts first
  • Automatic failover when one provider is down
  • Light usage on free or PRO credits

Together AI vs Hugging Face Inference Providers at a glance

AttributeTogether AIHugging Face Inference Providers
Model accessOpen weightsOpen weights
Flagship modelsKimi K3, DeepSeek V4, GLM 5.2, Qwen 3.8GLM 5.3, Kimi K3, DeepSeek V4.1 Flash
Speed0.99s TTFT on DeepSeek V4 ProRoutes to fastest provider by default
PriceParity with Fireworks and BasetenProvider rates, no markup
CustomizationLoRA and full SFT; RL in betaN/A
DeploymentServerless, dedicated, GPU clustersServerless router; dedicated Endpoints
Long context512K on DeepSeek V4 ProUp to 1M, provider-dependent

Frequently asked questions

What is the difference between Together AI and Hugging Face Inference Providers?

Together is one of the hosts Hugging Face routes to. Going direct adds fine-tuning, dedicated capacity and GPU clusters; the router adds choice and failover.

When should I choose Together AI over Hugging Face Inference Providers?

Fine-tuning or RL, then serving the checkpoint; Dedicated capacity with a 99% SLA; Reserved H100 clusters for training runs.

When should I choose Hugging Face Inference Providers over Together AI?

Checking Together against other hosts first; Automatic failover when one provider is down; Light usage on free or PRO credits.

Is Together AI or Hugging Face Inference Providers cheaper?

Together AI: Parity with Fireworks and Baseten. Hugging Face Inference Providers: Provider rates, no markup. The cheaper choice depends on the model and workload.

Which has more context, Together AI or Hugging Face Inference Providers?

Together AI: 512K on DeepSeek V4 Pro. Hugging Face Inference Providers: Up to 1M, provider-dependent.

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.

Subconscious vs Together AISubconscious vs Hugging Face Inference Providers