LLM Reference

OpenChat 3.5 Gemma

Released
2024-01-06
Last refreshed
2026-04-15
Status
Researched 154d ago

OpenChat 3.5 Gemma has model metadata, but missing tracked provider pricing keeps it from being a default production pick.

Use it for

  • Teams evaluating general LLM work
  • Workloads that can use a 8k context window

Do not use it for

  • Cost-sensitive launches that need sourced token pricing
  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Released
2024-01-06
Context
8k
Parameters
7B
Architecture
Decoder Only
Specialization
general
Training
finetuned
Created by

Human-centered approach to safe AI

N/A
Founded N/A
Website
Pricing

No tracked provider token pricing is available yet.

About

The OpenChat 3.5-0106-Gemma is a 7-billion parameter large language model celebrated for its impressive performance, particularly as the top Gemma variant. Developed by OpenChat, it uses the C-RLFT approach, training on the openchat-3.5-0106 dataset to handle mixed-quality data effectively without preference labels. It excels in diverse tasks like machine translation, code generation, and conversational AI, outperforming other versions and operating efficiently on consumer hardware with sufficient VRAM. However, users should be aware of potential hallucinations and biases, and ensure critical information from the model is verified.

OpenChat 3.5 Gemma is a model in the OpenChat 3 family. The structured metadata tracks a 8k-token context window. No headline benchmark score is tracked for OpenChat 3.5 Gemma yet.

Top use-case fit

No primary decision-task fit is mapped for this model yet.

Provider price ladder

No tracked provider token pricing is available for this model yet.

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.

Rankings & picks(5)