Logo Kopro AI
Kopro 3.0 Capabilities Architecture Languages Evaluations API Try it
New model · October 2026

Introducing Kopro 3.0

Our third generation, rebuilt on the Llama 3.2 architecture and tuned for natural conversation in English. Available today in Kopro Chat and the API.

Try Kopro 3.0 See evaluations
Kopro 3

A new foundation for Kopro

Every previous Kopro model was built on Qwen. With 3.0 we moved the family to a new foundation: Meta's Llama 3.2, fine-tuned by our team for the way people actually use Kopro.

Kopro 3.0 is a 3.2-billion-parameter model, quantized to 4-bit (Q4_K_M) so the whole model fits in about 2 GB. It runs on our own CPU servers rather than on a third-party model provider.

We tuned it on a curated set of a thousand conversations covering everyday advice, science explanations, practical tech help, cooking, culture and creative ideation. The goal was not to win leaderboards but to make Kopro feel more natural to talk to.

0B
parameters
0GB
on disk, 4-bit Q4_K_M
0K
token context in the architecture
0
token vocabulary
Capabilities

What Kopro 3.0 is good at

Natural conversation
Tuned on real dialogue rather than benchmark prompts, so answers read like a person talking, not a template.
English-first
Kopro 3.0 does its best work in English. For Russian and other languages, Kopro 2.0 gives noticeably better answers.
Everyday advice and explanations
Practical tech help, science explained simply, cooking, culture and life questions: the topics people bring to Kopro most.
Creative ideation
Brainstorms that skip the obvious answers. Ask for a project idea and you won't get another to-do app.
Calculations and finance
Solid on step-by-step arithmetic: ratios, margins, interest and unit conversions. See the evaluations below.
Runs on our own servers
Served from Kopro infrastructure, with web search, voice and the rest of Kopro Chat's tools around it.
Architecture

28 layers, grouped-query attention

Transformer blocks × 28 24 query heads share 8 key/value heads
Every 3 query heads share one key/value head, which keeps memory use low on small servers.

Kopro 3.0 keeps the Llama 3.2 3B design: 28 transformer blocks, a 3,072-wide hidden state and grouped-query attention. Rotary position embeddings with a base of 500,000 let the architecture handle up to 128K tokens.

Transformer blocks28
Hidden size3,072
Feed-forward size8,192
Attention heads (Q / KV)24 / 8
RoPE base500,000
Vocabulary128,256
QuantizationQ4_K_M · 2.0 GB

English only, for now

We want to be upfront: Kopro 3.0 does not speak Russian well. Its Llama 3.2 base was trained mostly on English, and our fine-tuning did not change that. In Russian it makes grammar mistakes, loses meaning and sometimes switches to English mid-answer.

If you write in Russian, choose Kopro 2.0 in the model menu. It is built on Qwen 2.5, handles Russian far better and is about twice as fast on our servers.

Recommended model
EnglishSupportedKopro 3.0
RussianWeakKopro 2.0
Other languagesNot testedKopro 2.0
Evaluations

How Kopro 3.0 performs

We ran Kopro 3.0 and Kopro 2.0 through the same set of 14 evaluations shown on our home page: 11 auto-graded questions each, temperature 0, identical prompts.

Kopro 3.0 Kopro 2.0
These are compact in-house proxy tests named after the benchmarks they are modeled on, not the official benchmark suites. Each has 11 short text questions, so one question moves a score by 9.1 points.

Generation speed on our servers

On our CPU servers Kopro 3.0 writes more slowly than its siblings: it trades speed for a newer architecture. For quick back-and-forth, Kopro Flash is still the fastest choice.

From 1.0 to 3.0

Kopro FlashLlama · 1.2B
Ultra-fast replies for chat loops and voice.
Kopro 2.0 · 2.0 ProQwen 2.5 · Qwen 2 Math
Next-gen reasoning and code, plus a math specialist.
Kopro 3.0Llama 3.2 · 3.2B
A new foundation, tuned for natural conversation in English.

Available in the API today

Use the model ID kopro-3.0 with our OpenAI-compatible endpoint. Existing integrations only need to change one line.

python
from openai import OpenAI

client = OpenAI(base_url="https://kopro.mom/v1", api_key="kp_live_...")

reply = client.chat.completions.create(
    model="kopro-3.0",
    messages=[{"role": "user", "content": "Hi! Who are you?"}],
)
print(reply.choices[0].message.content)

Start a conversation with Kopro 3.0

Open Kopro Chat and pick Kopro 3.0 from the model menu at the top.