LLM Reference

OpenOrca Models by Alignment Lab AI

10 models2023Up to 32k ctxFrom $0.2/1M input

About

The OpenOrca family of large language models (LLMs) leverages the Mistral 7B base model, fine-tuned with the OpenOrca dataset. This comprehensive dataset, mirroring the Orca Research Paper dataset, includes approximately 1 million GPT-4 completions and 3.2 million GPT-3.5 completions. OpenOrca models excel in a range of natural language processing tasks such as text and code generation, question answering, and conversations. Among these, the Mistral-7B-OpenOrca stands out for its superior performance among models with less than 30 billion parameters, achieving 98% of Llama2-70B-chat's performance on the HuggingFace leaderboard at its release. Designed to run efficiently on consumer-grade GPUs, these models are valuable tools for developers, though users should be mindful of potential biases inherent to the LLMs' training data1246810.

Current Variants

Use-when guidance is derived from seed capabilities, context, release, and replacement fields.

10 in view

Use when the workload needs 32k context and 56B parameters.

2023-1232k context56B parameters

Use when the workload needs 8k context and 7B parameters.

2023-108k context7B parameters

Use when the workload needs 8k context and 7B parameters.

2023-108k context7B parameters

Use when the workload needs 8k context and 7B parameters.

2023-108k context7B parameters

Use when the workload needs 4k context and 1.5B parameters.

2023-094k context1.5B parameters

Use when the workload needs 16k context and 13B parameters.

2023-0816k context13B parameters

Use when the workload needs 4k context and 13B parameters.

2023-084k context13B parameters

Use when the workload needs 16k context and 7B parameters.

2023-0816k context7B parameters

Use when the workload needs 4k context and 13B parameters.

2023-074k context13B parameters

Use when the workload needs 4k context and 13B parameters.

2023-074k context13B parameters

Release Timeline

5 release groups
2023-12
1 current
Mixtral 8x7B SlimOrca
32k context56B parameters
Current
2023-10
3 current
Mistral 7B OpenOrca
8k context7B parameters
Current
Mistral 7B OpenOrca Platypus
8k context7B parameters
Current
Mistral 7B SlimOrca
8k context7B parameters
Current
2023-09
1 current
OpenOrca Phi 1.5
4k context1.5B parameters
Current
2023-08
3 current
LlongOrca 13B 16K
16k context13B parameters
Current
LlongOrca 7B 16K
16k context7B parameters
Current
OpenOrca Platypus2 13B
4k context13B parameters
Current
2023-07
2 current
OpenOrca 13B
4k context13B parameters
Current
OpenOrca x OpenChat 13B
4k context13B parameters
Current

Specifications(10 models)

OpenOrca model specifications comparison
ModelReleasedContextParameters
Mixtral 8x7B SlimOrca2023-1232k56B
Mistral 7B SlimOrca2023-108k7B
Mistral 7B OpenOrca2023-108k7B
Mistral 7B OpenOrca Platypus2023-108k7B
OpenOrca Phi 1.52023-094k1.5B
LlongOrca 13B 16K2023-0816k13B
OpenOrca Platypus2 13B2023-084k13B
LlongOrca 7B 16K2023-0816k7B
OpenOrca x OpenChat 13B2023-074k13B
OpenOrca 13B2023-074k13B

Available From(2 providers)

Pricing

OpenOrca model pricing by provider
ModelProviderInput / 1MOutput / 1MType
Mistral 7B OpenOrcaTogether AI$0.2$0.2Serverless
Mistral 7B OpenOrcaFireworks AI$0.2$0.2Provisioned

Frequently Asked Questions

What is OpenOrca used for?
OpenOrca is used for coding. The family description and listed model capabilities point to those workloads as the best fit.
How does OpenOrca compare to OpenChat?
OpenOrca by Alignment Lab AI is strongest where you need coding, while OpenChat by Alignment Lab AI is the closest related family to check for coding. OpenOrca has 10 listed variants and reaches up to 32k context, while OpenChat reaches up to 8k context, so compare the specs and pricing tables before choosing a production model.
Which OpenOrca model should I use?
For the lowest listed input price, start with Mistral 7B OpenOrca through Fireworks AI at $0.2/1M input tokens. For the most capable/latest local choice, evaluate Mixtral 8x7B SlimOrca with 32k context.

Models(10)