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Model garden Router · on request Dedicated · available

Poro 34B

Runs as your own dedicated GPU deployment, ready to launch from the wizard. Data stays in Europe.

Poro is a 34B parameter decoder-only transformer pretrained on Finnish, English and code. It was trained on 1 trillion tokens. Poro is a fully open source model and is made available under the Apache 2.0 License.

Start for free ← All models
LumiOpen/Poro-34B vLLM ready
text->text · LumiOpen · sovereign EU
Runs on EU infrastructure operated by European companies; US marketplace capacity is never part of this chain. Full chain
34B
Parameters
—
Context window
160GB
Minimum VRAM
POST /api/v1/chat/completions On request

Specifications

Parameters 34B
Minimum VRAM 160 GB
Architecture BloomForCausalLM (vLLM)
License apache-2.0
Modality text->text
Released October 2023
Publisher LumiOpen ↗

Pricing

Shared router · per token
On request
Not available on the shared router. Pricing on request as a dedicated GPU deployment.
Dedicated GPU · per hour
from €6,97 per hour
Your own vLLM instance on European cloud (160 GB VRAM), billed hourly.

Shared EU router, pay-per-token, scale-to-zero. Dedicated GPU deployments are billed hourly, see pricing.

✓ Verified working on 01-08-2026, responded in 638 ms on our EU infrastructure.

Call it now

Drop-in replacement for OpenAI: change only the base URL and API key. The Anthropic format (/v1/messages) is supported too.

curl https://hostyourai.com/api/v1/chat/completions \
  -H "Authorization: Bearer hyai-..." \
  -H "Content-Type: application/json" \
  -d '{
    "model": "LumiOpen/Poro-34B",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Frequently asked questions

Can I run Poro 34B in the EU?

Yes. HostYourAI runs Poro 34B on GPUs in European datacenters via vLLM. Prompts and outputs never leave the EU and there is no US cloud provider in the chain.

Is hosting Poro 34B GDPR-compliant?

Yes. All processing happens inside the EU, a Data Processing Agreement (DPA) is available and the subprocessor list is public. Open-source weights also mean: no training on your data.

How much does Poro 34B cost?

Poro 34B needs several GPUs at once, so it runs as a dedicated deployment billed per GPU-hour rather than per token. Tell us your volume and we will work it out with you.

Is the API OpenAI-compatible?

Yes. You use the standard OpenAI SDKs with a custom base URL (https://hostyourai.com/api/v1). The Anthropic Messages API is supported as a drop-in as well.

More models from LumiOpen

Llama Poro 2 8B Long Instruct

Poro 2 Long Instruct is an instruction-following chatbot model with extended context support, created through supervised fine-tuning (SFT) of the Poro 2 Long Base model followed by merging the SFT checkpoint back with the base model to preserve long-context performance. This model is designed for conversational AI applications and instruction following in both Finnish and English, with support for context lengths up to 128K tokens. It was trained on a carefully curated mix of English and Finnish instruction data.

8B 131K context View model →
Llama Poro 2 8B Long Math Reasoning RL Preview

Poro 2 8B Math Reasoning RL Preview is a specialized model focused on mathematical reasoning and problem-solving. This preview model was created through reinforcement learning (RL) on top of the Math Reasoning SFT checkpoint. This model excels at mathematical reasoning tasks but is not optimized for general conversational use or other domains.

8B 131K context View model →
Llama Poro 2 8B Long Base

Poro 2 Long Base is an 8B parameter decoder-only transformer created by extending Poro 2 8B Base from an 8K to 128K token context window using LongRoPE. The model supports both English and Finnish with an extended context window of 128K tokens. Poro 2 Long Base is released as a fully open source model under the Llama 3.1 Community License.

8B 131K context View model →
Llama Poro 2 8B Long Math Reasoning SFT Preview

Poro 2 8B Math Reasoning SFT Preview is a specialized model focused on mathematical reasoning and problem-solving. This preview model was created through supervised fine-tuning of a context-extended base model. This model excels at mathematical reasoning tasks but is not optimized for general conversational use or other domains.

8B 131K context View model →
Llama Poro 2 70B SFT

Note for most users: This is an intermediate checkpoint from our post-training pipeline. Most users should use Poro 2 70B Instruct instead, which includes an additional round of Direct Preference Optimization (DPO) for improved response quality and alignment. This SFT-only model is primarily intended for researchers interested in studying the effects of different post-training techniques.

71B 8K context View model →
Llama Poro 2 8B SFT

Note for most users: This is an intermediate checkpoint from our post-training pipeline. Most users should use Poro 2 8B Instruct instead, which includes an additional round of Direct Preference Optimization (DPO) for improved response quality and alignment. This SFT-only model is primarily intended for researchers interested in studying the effects of different post-training techniques.

8B 8K context View model →

Try Poro 34B for free

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