Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support, with the following key features: - Uniquely support of seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue) within single model, ensuring optimal performance across various scenarios. - Significantly enhancement in its reasoning capabilities, surpassing previous QwQ (in thinking mode) and…
Open-weight model · Text generation
Symbiotic-8B
by Convergent Intelligence reaperdoesntknow/Symbiotic-8B
Symbiotic-8B is an open-weight model for text generation from Convergent Intelligence, released under afl-3.0. It has 8.2B parameters and a 40,960-token context. At 16-bit it needs about 19.7 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 4.5k downloads a month.
Purpose: Long-memory symbolic reasoning + high-fidelity language generation SymbioticLM-8B is a state-of-the-art hybrid transformer model with built-in symbolic cognition.
Parameters8.2B
Context40,960
Weights43.0 GB
Licenseafl-3.0
AccessOpen weights
Monthly Downloads4.5k
Runs On
What it takes to serve Symbiotic-8B (8.2B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 16.4 GB | 19.7 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 8.2 GB | 9.8 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 4.1 GB | 4.9 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 9, 2026.
Symbiotic-8B on every accelerator the SAVRN Index prices, at every precision
Model Card
By Convergent Intelligence, published under afl-3.0, revision d3a0eef9fb18.
SymbioticLM-8B
Model Type: Hybrid Symbolic–Transformer
Base Model: Qwen-8B
Framework: PyTorch + Transformers-compatible
Purpose: Long-memory symbolic reasoning + high-fidelity language generation
Overview
SymbioticLM-8B is a state-of-the-art hybrid transformer model with built-in symbolic cognition. It combines an 8B Qwen-based transformer with modular symbolic processors and a persistent memory buffer. The model supports both general conversation and deep symbolic tasks such as theorem generation, logical chaining, and structured reasoning with retained memory across turns.
Architecture Highlights
- Backbone: Qwen-8B rotary transformer
- Symbolic Dim: 4096
- Symbolic Modules:
- ThoughtDynamicsLNN (multi-head LSTM attention)
- CrystallineProcessor (DNAConv GNN)
- LiquidThoughtProcessor (recurrent symbol folding)
- HelicalDNAProcessor (helical linear projection)
- Memory: 2048 symbolic vectors (float32) with entropy-aware retrieval and contextual recall
- Dream Mode: Self-generates symbolic cognition offline
Files Included
Configuration
- Architecture
- Qwen3ForCausalLM
- Context length (tokens)
- 40,960
- Layers
- 36
- Hidden size
- 4,096
- Feed-forward size
- 12,288
- Attention heads
- 32
- Key/value heads
- 8
- Head dimension
- 128
- Vocabulary size
- 151,936
- RoPE base
- 1,000,000
- Stored precision
- bfloat16
- Model type
- qwen3
Identity and Version
- Repository
- reaperdoesntknow/Symbiotic-8B
- Publisher
- Convergent Intelligence
- Task
- Text generation
- Modality
- Text
- Library
- transformers
- Parameters
- 8.2B parameters
- Languages
- en
- Revision
- d3a0eef9fb185fdcebdc9e61d6a52064dc52be7d
- First published
- 2025-05-06
- Last updated
- 2026-09-18
Files and Weights
19 files, 43.1 GB in total. The weights are 8 files totalling 43.0 GB in bin, safetensors.
Weights8 files · 43.0 GB
Configuration5 files · 36.9 KB
Tokenizer4 files · 15.9 MB
Documentation1 file · 6.5 KB
Repository1 file · 1.6 KB
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model-00001-of-00007.safetensors | Weights | 5.0 GB | ef9b808bfd5c |
| model-00002-of-00007.safetensors | Weights | 4.8 GB | 16dc83b78630 |
| model-00003-of-00007.safetensors | Weights | 4.8 GB | dd4ed71c9a98 |
| model-00004-of-00007.safetensors | Weights | 5.0 GB | 9d0d4a0e3852 |
| model-00005-of-00007.safetensors | Weights | 4.8 GB | 9a1256a3c728 |
| model-00006-of-00007.safetensors | Weights | 4.8 GB | ecbff6633142 |
| model-00007-of-00007.safetensors | Weights | 3.5 GB | a73aac17dc52 |
| model.bin | Weights | 10.3 GB | f6cb74dc6bfb |
| added_tokens.json | Configuration | 707 B | — |
| config.json | Configuration | 769 B | — |
| generation_config.json | Configuration | 1.9 KB | — |
| model.safetensors.index.json | Configuration | 32.9 KB | — |
| special_tokens_map.json | Configuration | 613 B | — |
| README.md | Documentation | 6.5 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| merges.txt | Tokenizer | 1.7 MB | — |
| tokenizer.json | Tokenizer | 11.4 MB | aeb13307a71a |
| tokenizer_config.json | Tokenizer | 9.7 KB | — |
| vocab.json | Tokenizer | 2.8 MB | — |
License and Download
- License
- afl-3.0
- Access
- Open weights, no gate
- Download size
- 43.0 GB
Download from Convergent Intelligence
Released by Convergent Intelligence through its official repository on Hugging Face.
Built From
- Derived from Qwen/Qwen3-8B
- Trained on (disclosed) 0xZee/dataset-CoT-Advanced-Calculus-268
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 43.0 GB |
| 16-bit | 16.4 GB |
| 8-bit | 8.2 GB |
| 4-bit | 4.1 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About Symbiotic-8B
How much GPU memory does Symbiotic-8B need?
About 19.7 GB at 16-bit and 4.9 GB at 4-bit: the weights (8.2B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run Symbiotic-8B on?
At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
What license is Symbiotic-8B released under?
afl-3.0, as its publisher declares it. Read the license text before commercial use.
What is Symbiotic-8B's context length?
40,960 tokens, from the maximum position embeddings in its published configuration.
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