Model library / Blockway
Agens Volundr 32B Preview is an open-weight 32.7 billion-parameter model from Blockway for reasoning, coding and agent-oriented tasks.
Parameters in total
Context length in tokens, as published
Weights at the released precision
Licence declared on the repository
Overview
The model is a 32-billion-parameter VolundrForConditionalGeneration released as a preview by Blockway. It is intended for reasoning, code generation, and agent work, handling English, Simplified and Traditional Chinese, Cantonese, text and images, and uses Blockway's control-token chat format with tool-call support.
In practice the model occupies roughly 32.7 B parameters, accepts up to 262,144 tokens of context, and is distributed under the Apache-2.0 licence. Weights are not published. It runs on Blockway's sglang build, typically bf16 on two 48 GB GPUs, with flat decode cost across long contexts and optional speculative decoding for speed gains.
Specification
| Repository | Blockway/Agens-Volundr-32B-Preview |
| Publisher | Blockway |
| Published | 3 October 2026 |
| Architecture | VolundrForConditionalGeneration |
| Model type | volundr |
| Parameters | 32,688,700,242 |
| Layers | 72 |
| Hidden size | 5,120 |
| Attention heads | 24, 4 key/value heads |
| Context length | 262,144 tokens |
| Vocabulary | 248,320 tokens |
| Licence | apache-2.0 |
Memory
Parameter count multiplied by the bytes each format uses. The key-value cache comes on top.
| Precision | Weights | Notes |
|---|---|---|
| bf16 | 60.9 GiB | Full precision as released |
| fp8 | 30.4 GiB | 8-bit, near-lossless on most models |
| int4 | 15.2 GiB | 4-bit, smallest footprint |
The cache costs 288 KiB per token at 16-bit, so the full 262,144-token context of one request needs about 72.0 GiB. Concurrency multiplies that number, not the weights.
Hardware
At the released precision, with 90% of the card given to the server and 2.5 GiB kept for the runtime. The context column is what is left for the cache on that setup.
| GPU | Cards needed | Free for cache | Context it holds |
|---|---|---|---|
| RTX 4090 24GB | 4 | 15.5 GiB | about 56,479 tokens |
| RTX 5090 32GB | 4 | 44.3 GiB | about 161,337 tokens |
| L40S 48GB | 2 | 20.5 GiB | about 74,683 tokens |
| A100 80GB | 1 | 8.6 GiB | about 31,357 tokens |
| H100 80GB | 1 | 8.6 GiB | about 31,357 tokens |
| RTX PRO 6000 96GB | 1 | 23.0 GiB | about 83,786 tokens |
| H200 141GB | 1 | 63.5 GiB | about 231,242 tokens |
Serving
A vLLM launch line for the shape above. Check the model card for a runtime the publisher recommends.
vllm serve Blockway/Agens-Volundr-32B-Preview \ --max-model-len 53248 \ --gpu-memory-utilization 0.90
Questions
The weights take about 61 GiB at the released precision. That fits on one A100 80GB, which leaves roughly 9 GiB for the key-value cache.
The repository declares apache-2.0. Read the licence text before commercial use: the name alone does not tell you what is allowed.
The configuration allows 262,144 tokens. Whether the whole window is usable depends on the memory left for the cache, which the hardware table works out per card.
This page is a reference, and Aiqre does not serve this model today. We deploy open-weight models on dedicated EU hardware on request, so if you want an OpenAI-compatible endpoint for it, email [email protected] with the model name and roughly what volume you expect.
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Hosting
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