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Fireworks AI vs Venice
Fireworks sells measured speed and post-training on open models. Venice sells privacy guarantees and uncensored models, and publishes no speed data.
By The Subconscious Team · Updated
Fireworks AI vs Venice: key differences
Fireworks has the numbers Venice lacks. Third-party tests put Fireworks at 167 to 174 tokens per second on DeepSeek V4 Pro, with full 1M context on that model, across a 400+ model catalog. Venice lists 370+ models, including GLM 5.3, Kimi K3 and DeepSeek V4, with 1M context on most current models, but it publishes no throughput figures. What Venice offers instead is a privacy model: contract-enforced zero data retention on open models, TEE and end-to-end encrypted inference on some, and anonymized proxy access to Claude, GPT and Gemini. Fireworks answers compliance buyers differently, with SOC 2, HIPAA and ISO certifications and billing through the AWS and GCP marketplaces.
Customization is the other clear gap. Fireworks runs SFT, DPO and reinforcement fine-tuning, serves fine-tuned models at base-model prices, and made its Training API generally available in August 2026 for teams running their own RL loops. Venice offers no customer training, though its own uncensored fine-tunes cover content other hosts filter out. On price, Fireworks sits above bargain hosts on small commodity models, and its dedicated H100 rate rose to $8 an hour on September 1. Venice starts at $0.06 in on GLM 4.7 Flash and adds crypto, USDC and DIEM payment. Latency-sensitive production agents fit Fireworks; private or unfiltered consumer apps fit Venice.
What Fireworks AI and Venice do
Fireworks AI
Fireworks AI was founded in 2022 by former Meta PyTorch engineers led by CEO Lin Qiao, and it sells speed on open models. Its custom serving stack has posted 167 to 174 tokens per second on DeepSeek V4 Pro in third-party measurements, several times what most GPU peers hit on the same model. The catalog holds 400+ models across text, vision, audio and embeddings, served through an OpenAI-compatible API. In July 2026 it raised a $1.505B Series D at a $17.5B valuation, with a reported $1B+ run rate and 40T+ tokens a day.
Example models: DeepSeek V4 Pro, Kimi K3
Full Fireworks AI profileVenice
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.
Example models: GLM 5.3, Kimi K3, Venice Uncensored 1.2
Full Venice profileShould you choose Fireworks AI or Venice?
Fireworks AI
Choose Fireworks AI for
- Latency-sensitive tool-calling agents
- Reinforcement fine-tuning served at base price
- Buyers needing SOC 2, HIPAA and marketplace billing
Venice
Choose Venice for
- Zero-retention and TEE inference on open models
- Uncensored models for creative products
- Mixing open and proxied closed models on one key
Fireworks AI vs Venice at a glance
| Attribute | Fireworks AI | Venice |
|---|---|---|
| Model access | Open weights | Open weights, plus proxied closed models |
| Flagship models | DeepSeek V4 Pro, Kimi K3 | GLM 5.3, Kimi K3, DeepSeek V4 Pro |
| Speed | 167–174 tok/s on DeepSeek V4 Pro | Unknown |
| Price | Fine-tunes served at base price | $0.06–$12 in, $0.28–$60 out per 1M; DIEM staking |
| Customization | SFT, DPO, RFT; Training API | Unknown |
| Deployment | Serverless, dedicated GPUs | Serverless API, consumer app |
| Long context | Full 1M on DeepSeek V4 Pro | 1M on most current models |
Frequently asked questions
What is the difference between Fireworks AI and Venice?
Fireworks sells measured speed and post-training on open models. Venice sells privacy guarantees and uncensored models, and publishes no speed data.
When should I choose Fireworks AI over Venice?
Latency-sensitive tool-calling agents; Reinforcement fine-tuning served at base price; Buyers needing SOC 2, HIPAA and marketplace billing.
When should I choose Venice over Fireworks AI?
Zero-retention and TEE inference on open models; Uncensored models for creative products; Mixing open and proxied closed models on one key.
Is Fireworks AI or Venice cheaper?
Fireworks AI: Fine-tunes served at base price. 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, Fireworks AI or Venice?
Fireworks AI: Full 1M on DeepSeek V4 Pro. Venice: 1M on most current models.
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