Meet-MoE1-500M-A100M-Stage2 is an open-weight model from M7. It has 499M parameters and a 65,536-token context. At 16-bit it needs about 1.2 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
Runs On
What it takes to serve Meet-MoE1-500M-A100M-Stage2 (499M 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 | 1.0 GB | 1.2 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.5 GB | 0.6 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.2 GB | 0.3 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 18, 2026.
Meet-MoE1-500M-A100M-Stage2 on every accelerator the SAVRN Index prices, at every precision
Model Card
The publisher has not written a card for this model.
Configuration
- Architecture
- Qwen3MoeForCausalLM
- Context length (tokens)
- 65,536
- Layers
- 20
- Hidden size
- 768
- Feed-forward size
- 2,048
- Attention heads
- 12
- Key/value heads
- 4
- Vocabulary size
- 32,768
- Experts
- 20
- Experts active per token
- 2
- RoPE base
- 1e+06
- Model type
- qwen3_moe
Identity and Version
- Repository
- Ma7ee7/Meet-MoE1-500M-A100M-Stage2
- Publisher
- M7
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 499M parameters
- Languages
- Not stated by the source
- Revision
- 2aea324463d9df73cd1825995034444fa4de4362
- First published
- 2026-10-15
- Last updated
- 2026-10-15
Files and Weights
9 files, 2.0 GB in total. The weights are 1 file totalling 2.0 GB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 2.0 GB | a08a4715db88 |
| config.json | Configuration | 917 B | — |
| generation_config.json | Configuration | 154 B | — |
| special_tokens_map.json | Configuration | 555 B | — |
| stage2_metadata.json | Configuration | 551 B | — |
| README.md | Documentation | 115 B | — |
| .gitattributes | Repository | 1.5 KB | — |
| tokenizer.json | Tokenizer | 2.3 MB | — |
| tokenizer_config.json | Tokenizer | 947 B | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 2.0 GB
Released by M7 through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 2.0 GB |
| 16-bit | 1.0 GB |
| 8-bit | 0.5 GB |
| 4-bit | 0.2 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About Meet-MoE1-500M-A100M-Stage2
How much GPU memory does Meet-MoE1-500M-A100M-Stage2 need?
About 1.2 GB at 16-bit and 0.3 GB at 4-bit: the weights (499M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run Meet-MoE1-500M-A100M-Stage2 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 is Meet-MoE1-500M-A100M-Stage2's context length?
65,536 tokens, from the maximum position embeddings in its published configuration.