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  1. Models
  2. Text
  3. Envoid

Llama 3.05 Storybreaker Ministral 70b

Much more inclined to output adult content than its predecessor. Great choice for novelty roleplay scenarios.

Pricing

Auto routing · per 1M tokens
Input
$0.493
Output
$0.493
Cache read
$0.246
Compare provider prices

Specifications

Context window
16.4K
Max output
8.2K
Parameters
70B

Benchmarks

No public benchmark scores for this model yet.

Providers

Auto routing is available for this model. Explicit provider selection is not available.

Auto
Auto
Recommended
$0.493$0.493$0.246N/AN/A
Batch API
ProviderInputOutputCached input
Auto
AutoEnvoid/Llama-3.05-NT-Storybreaker-Ministral-70B
$0.493/M$0.493/M$0.246/M

Batch rows for this model use normal routing and cost the same as standard API requests. Set provider in a row to choose a provider.

Reliability

Related text models

Compare Llama 3.05 Storybreaker Ministral 70b with similar models from the same provider or model family.

Nemotron Tenyxchat Storybreaker 70b

Envoid/Llama-3.05-Nemotron-Tenyxchat-Storybreaker-70B

Overall it provides a solid option for RP and creative writing while still functioning as an assistant model, if desired. If used to continue a roleplay it will generally follow the ongoing cadence of the conversation.

Llama 3.3 70B Instruct abliterated

huihui-ai/Llama-3.3-70B-Instruct-abliterated

An abliterated (removed restrictions and censorship) version of Llama 3.3 70b.

Llama 3 70B abliterated

failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5

An abliterated (removed restrictions and censorship) version of Llama 3.1 70b.

Llama 3.3 70B

TEE/llama3-3-70b

Meta's Llama 3.3 with 70B parameters. TEE-backed inference with provider attestation support.

Llama-xLAM-2 70B fc-r

Salesforce/Llama-xLAM-2-70b-fc-r

Salesforce’s 70-B frontier model focused on function-calling & retrieval-augmented generation.

Llama 3.3 70b Instruct

meta-llama/llama-3.3-70b-instruct

Llama 3.3 is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks.