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Favicon for venice

Venice: Uncensored

cognitivecomputations/dolphin-mistral-24b-venice-edition

Model weights
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Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving user control over alignment, system prompts, and behavior. Intended for advanced and unrestricted use cases, Venice Uncensored emphasizes steerability and transparent behavior, removing default safety and alignment layers typically found in mainstream assistant models.

Modalities
In / Out Price
$0.20 / $0.90per 1M
Context
128K
Released
Jul 9, 2025
Knowledge Cutoff
Apr 2024
Compare
ProvidersPricingPerformanceUptimeAppsActivityFAQExplore

Providers

This model is hosted by one provider. OpenRouter forwards every request to it directly — no routing decisions to make.

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

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AI Model RankingsRanking
$0.20$0.900.65s48 tps
100.00%
Throughput
48tok/s

P50, best across providers

Latency
0.65s

P50, best provider

Uptime (3d)The model was reachable. Request routed to a provider.
100.00%
Availability (3d)The model returned inference from any provider. Errors and empty responses count against it.
99.96%

Availability over the last 3 days

Last 72 hours
Availability 99.96%
3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability
99.98%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.

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Frequently asked questions

Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving user control over alignment, system prompts, and behavior.

Uncensored costs $0.20/M input tokens and $0.90/M output tokens.

Uncensored has a 128,000 token context window. It supports up to 8,192 completion tokens.

No. Uncensored does not accept tools, so function calling is unavailable. It supports response_format for JSON output, without JSON-schema enforcement.

Uncensored was released on July 9, 2025. Its knowledge cutoff is April 30, 2024.

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Dolphin3.0 R1 Mistral 24B

Dolphin 3.0 R1 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases.

The R1 version has been trained for 3 epochs to reason using 800k reasoning traces from the Dolphin-R1 dataset.

Dolphin aims to be a general purpose reasoning instruct model, similar to the models behind ChatGPT, Claude, Gemini.

Part of the Dolphin 3.0 Collection Curated and trained by Eric Hartford, Ben Gitter, BlouseJury and DphnAI

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Dolphin3.0 Mistral 24B

Dolphin 3.0 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases.

Dolphin aims to be a general purpose instruct model, similar to the models behind ChatGPT, Claude, Gemini.

Part of the Dolphin 3.0 Collection Curated and trained by Eric Hartford, Ben Gitter, BlouseJury and DphnAI

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Dolphin Llama 3 70B 🐬

Dolphin 2.9 is designed for instruction following, conversational, and coding. This model is a fine-tune of Llama 3 70B. It demonstrates improvements in instruction, conversation, coding, and function calling abilities, when compared to the original.

Uncensored and is stripped of alignment and bias, it requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at erichartford.com/uncensored-models.

Usage of this model is subject to Meta's Acceptable Use Policy.

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Dolphin 2.9.2 Mixtral 8x22B 🐬

Dolphin 2.9 is designed for instruction following, conversational, and coding. This model is a finetune of Mixtral 8x22B Instruct. It features a 64k context length and was fine-tuned with a 16k sequence length using ChatML templates.

This model is a successor to Dolphin Mixtral 8x7B.

The model is uncensored and is stripped of alignment and bias. It requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at erichartford.com/uncensored-models.

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Dolphin 2.6 Mixtral 8x7B 🐬

This is a 16k context fine-tune of Mixtral-8x7b. It excels in coding tasks due to extensive training with coding data and is known for its obedience, although it lacks DPO tuning.

The model is uncensored and is stripped of alignment and bias. It requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at erichartford.com/uncensored-models.

#moe #uncensored

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