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Groq vs Venice
Groq is built for speed on a handful of models. Venice is built for privacy across hundreds, with 1M context where Groq caps near 131K.
By The Subconscious Team · Updated
Groq vs Venice: key differences
Groq's pitch is time. Its LPU publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B, with tail latency close to the median, and it hosts Whisper plus an agentic system called Groq Compound. The catch is a small, shrinking catalog capped around 131K context, after Llama 3.3 70B and Llama 3.1 8B shut down in August 2026. Venice goes the other way on breadth, with 370+ models across text, image, audio and video and 1M context on most current models, including GLM 5.3, Kimi K3 and DeepSeek V4. It publishes no speed numbers, so a direct latency test is worth running before assuming anything close to Groq.
Privacy and content policy are where Venice leads. Open models run under contract-enforced zero data retention, some with TEE or end-to-end encrypted inference, and Venice's uncensored fine-tunes serve products other hosts filter. Groq competes on cost at the small end, with per-token prices near the market floor and stacking cache and Batch discounts, while Venice starts at $0.06 in on GLM 4.7 Flash and can be paid in crypto or through DIEM staking. Neither hosts customer fine-tunes. Groq's long-term direction is also an open question after NVIDIA licensed the LPU and hired most of its engineers. Voice agents belong on Groq; long-context private chat fits Venice.
What Groq and Venice do
Groq
Groq serves open models on its own chip, the LPU, which keeps model weights in on-chip SRAM and runs a deterministic schedule instead of waiting on GPU memory. Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B. Latency stays tight between median and tail, which matters for strict SLAs. The API is OpenAI-compatible and also hosts Whisper for speech to text plus an agentic system called Groq Compound with built-in search and code execution.
Example models: GPT-OSS 120B, Qwen 3.6 27B
Full Groq 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 Groq or Venice?
Groq vs Venice at a glance
| Attribute | Groq | Venice |
|---|---|---|
| Model access | Open weights | Open weights, plus proxied closed models |
| Flagship models | GPT-OSS 120B, Qwen 3.6 27B | GLM 5.3, Kimi K3, DeepSeek V4 Pro |
| Speed | 500–1,000 tok/s | Unknown |
| Price | Near the floor on small models | $0.06–$12 in, $0.28–$60 out per 1M; DIEM staking |
| Customization | No fine-tuned model hosting | Unknown |
| Deployment | GroqCloud API | Serverless API, consumer app |
| Long context | Around 131K max | 1M on most current models |
Frequently asked questions
What is the difference between Groq and Venice?
Groq is built for speed on a handful of models. Venice is built for privacy across hundreds, with 1M context where Groq caps near 131K.
When should I choose Groq over Venice?
Voice agents pairing Whisper with fast replies; Tight agent loops where each step must return fast; Strict SLAs judged on tail latency.
When should I choose Venice over Groq?
Prompts longer than Groq's 131K cap; Private chat on large open models like Kimi K3; Uncensored creative apps.
Is Groq or Venice cheaper?
Groq: Near the floor on small models. 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, Groq or Venice?
Groq: Around 131K max. Venice: 1M on most current models.
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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.