Open-weight model
e2e-terminal-rl-qwen35-4b-slime-sb-XpAvCqbu2T1wSFs1zgsNlP
by Qijia Shen qijiashen/e2e-terminal-rl-qwen35-4b-slime-sb-XpAvCqbu2T1wSFs1zgsNlP
e2e-terminal-rl-qwen35-4b-slime-sb-XpAvCqbu2T1wSFs1zgsNlP is an open-weight model from Qijia Shen. It has 2.3B parameters and a 262,144-token context. At 16-bit it needs about 5.5 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
submission weights 82a9abb43065 at elapsed 23629s: run6 iter38, eval T0.8/topp0.95/topk50 (dev 14/64) Ungraded backup of a benchmark agent's submission (SUBMISSION.json lists the file sha256s).
Runs On
What it takes to serve e2e-terminal-rl-qwen35-4b-slime-sb-XpAvCqbu2T1wSFs1zgsNlP (2.3B 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 | 4.5 GB | 5.5 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 2.3 GB | 2.7 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 1.1 GB | 1.4 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.
Model Card
submission weights 82a9abb43065 at elapsed 23629s: run6 iter38, eval T0.8/topp0.95/topk50 (dev 14/64) Ungraded backup of a benchmark agent's submission (SUBMISSION.json lists the file sha256s).
Excerpt from the card by Qijia Shen.
Configuration
- Architecture
- Qwen3_5ForConditionalGeneration
- Context length (tokens)
- 262,144
- Layers
- 24
- Hidden size
- 2,048
- Feed-forward size
- 6,144
- Attention heads
- 8
- Key/value heads
- 2
- Head dimension
- 256
- Vocabulary size
- 248,320
- Model type
- qwen3_5
Identity and Version
- Repository
- qijiashen/e2e-terminal-rl-qwen35-4b-slime-sb-XpAvCqbu2T1wSFs1zgsNlP
- Publisher
- Qijia Shen
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 2.3B parameters
- Languages
- Not stated by the source
- Revision
- 23f27c2010641b359b8a0c47e50dcab4a6e40d10
- First published
- 2026-10-04
- Last updated
- 2026-10-05
Files and Weights
13 files, 4.6 GB in total. The weights are 1 file totalling 4.5 GB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 4.5 GB | 82a9abb43065 |
| SUBMISSION.json | Configuration | 6.1 KB | — |
| config.json | Configuration | 2.9 KB | — |
| eval_config.json | Configuration | 104 B | — |
| preprocessor_config.json | Configuration | 390 B | — |
| video_preprocessor_config.json | Configuration | 385 B | — |
| README.md | Documentation | 239 B | — |
| chat_template.jinja | Other | 7.8 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| merges.txt | Tokenizer | 3.4 MB | — |
| tokenizer.json | Tokenizer | 12.8 MB | 5f9e4d4901a9 |
| tokenizer_config.json | Tokenizer | 16.7 KB | — |
| vocab.json | Tokenizer | 6.7 MB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 4.5 GB
Released by Qijia Shen through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 4.5 GB |
| 16-bit | 4.5 GB |
| 8-bit | 2.3 GB |
| 4-bit | 1.1 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About e2e-terminal-rl-qwen35-4b-slime-sb-XpAvCqbu2T1wSFs1zgsNlP
How much GPU memory does e2e-terminal-rl-qwen35-4b-slime-sb-XpAvCqbu2T1wSFs1zgsNlP need?
About 5.5 GB at 16-bit and 1.4 GB at 4-bit: the weights (2.3B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run e2e-terminal-rl-qwen35-4b-slime-sb-XpAvCqbu2T1wSFs1zgsNlP 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 e2e-terminal-rl-qwen35-4b-slime-sb-XpAvCqbu2T1wSFs1zgsNlP's context length?
262,144 tokens, from the maximum position embeddings in its published configuration.