# Together AI vs Venice

> Together AI is where teams train and serve open models at scale. Venice is where they call open models privately, with no fine-tuning but uncensored options.

Canonical: https://www.subconscious.dev/compare/together-ai-vs-venice · By The Subconscious Team · Updated September 30, 2026

## How they compare

The two overlap on hosted open models. Together serves more than thirty, including Kimi K3, DeepSeek V4, GLM 5.2 and Qwen 3.8, with 512K context on DeepSeek V4 Pro and a measured 0.99s time to first token on it. Venice lists GLM 5.3, Kimi K3 and DeepSeek V4 with 1M context on most current models, under contract-enforced zero retention, and adds TEE and end-to-end encrypted inference on some. Venice's catalog is larger at 370+ models partly because it also proxies closed models from Anthropic, OpenAI and Google. Venice publishes no speed figures, so teams that care about latency should benchmark it against Together on their own prompts.

Customization is where Together pulls ahead. It offers LoRA and full-parameter SFT from $0.48 per million training tokens, reinforcement learning in closed beta, dedicated deployments, provisioned throughput with a 99% SLA, and H100 clusters from $3.19 an hour reserved. Venice has no fine-tuning for customers, though it ships its own uncensored fine-tunes like Venice Uncensored 1.2. Together has no free tier. Venice's DIEM staking offers a daily credit allowance, and it takes crypto and USDC per request. A team building a custom model on proprietary data belongs on Together. A team calling stock open models with sensitive or unfiltered prompts may prefer Venice.

## What each one does

### 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.

### Venice

Venice is a privacy-focused AI platform founded in 2024 by Erik Voorhees, the crypto entrepreneur behind ShapeShift. It pairs a consumer chat app with a developer API that works as a drop-in replacement for OpenAI's chat endpoint and covers text, image, audio and video across 370+ models. Open models such as GLM 5.3, Kimi K3, DeepSeek V4 and Venice's own uncensored fine-tunes run under a private tier with contract-enforced zero data retention, and some add TEE inference or end-to-end encryption, where only an attested enclave can decrypt the prompt. Closed models from Anthropic, OpenAI and Google are proxied under an anonymized tier that hides user identity but leaves prompt content visible to the upstream provider.

## Which is best, and when

### Choose Together AI for

- Fine-tuning or RL, then serving the checkpoint
- Reserved GPU clusters for large experiments
- Production rollouts with canary and A/B routing

### Choose Venice for

- Zero-retention calls to Kimi K3 and GLM 5.3
- Open and closed models behind one key
- Crypto-funded inference budgets

## At a glance

| Attribute | Together AI | Venice |
|---|---|---|
| Model access | Open weights | Open weights, plus proxied closed models |
| Flagship models | Kimi K3, DeepSeek V4, GLM 5.2, Qwen 3.8 | GLM 5.3, Kimi K3, DeepSeek V4 Pro |
| Speed | 0.99s TTFT on DeepSeek V4 Pro | - |
| Price | Parity with Fireworks and Baseten | $0.06–$12 in, $0.28–$60 out per 1M; DIEM staking |
| Customization | LoRA and full SFT; RL in beta | - |
| Deployment | Serverless, dedicated, GPU clusters | Serverless API, consumer app |
| Long context | 512K on DeepSeek V4 Pro | 1M on most current models |

## FAQ

### What is the difference between Together AI and Venice?

Together AI is where teams train and serve open models at scale. Venice is where they call open models privately, with no fine-tuning but uncensored options.

### When should I choose Together AI over Venice?

Fine-tuning or RL, then serving the checkpoint; Reserved GPU clusters for large experiments; Production rollouts with canary and A/B routing.

### When should I choose Venice over Together AI?

Zero-retention calls to Kimi K3 and GLM 5.3; Open and closed models behind one key; Crypto-funded inference budgets.

### Is Together AI or Venice cheaper?

Together AI: Parity with Fireworks and Baseten. Venice: $0.06–$12 in, $0.28–$60 out per 1M; DIEM staking. The cheaper choice depends on the model and workload.

### Which has more context, Together AI or Venice?

Together AI: 512K on DeepSeek V4 Pro. Venice: 1M on most current models.

## Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious: [Subconscious vs Together AI](https://www.subconscious.dev/compare/subconscious-vs-together-ai.md), [Subconscious vs Venice](https://www.subconscious.dev/compare/subconscious-vs-venice.md).

Full profiles: [Together AI](https://www.subconscious.dev/providers/together-ai.md), [Venice](https://www.subconscious.dev/providers/venice.md).