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Open-weight model · Text generation

cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c

by Alexander Gurung agurung/cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c

cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c is an open-weight model for text generation from Alexander Gurung. It has 4.4B parameters and a 262,144-token context. At 16-bit it needs about 10.6 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 183 downloads a month.

An OpenRLHF GRPO reinforcement-learning checkpoint for Qwen3-4B. - Saved at global step 66 of RL run seededrlbaseramp25stoppengen4kep2ncp5baseq3c. - This is the best checkpoint by pass@8 so far in this run.

Parameters4.4B
Context262,144
Weights8.8 GB
License—
AccessOpen weights
Monthly Downloads183

Runs On

What it takes to serve cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c (4.4B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 8.8 GB 10.6 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 4.4 GB 5.3 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 2.2 GB 2.6 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 24, 2026.

cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c on every accelerator the SAVRN Index prices, at every precision

Model Card

An OpenRLHF GRPO reinforcement-learning checkpoint for Qwen3-4B. - Saved at global step 66 of RL run seededrlbaseramp25stoppengen4kep2ncp5baseq3c. - This is the best checkpoint by pass@8 so far in this run. Trained and validated on the cobalt-train ≤2/64 frontier (canonical cleaneval prompts): 1833 train / 112 held-out val problems the base model solved on at most 2 of 64 samples under the iidcanonical@64 hardness scan. Val evals sample at temperature 1.0 (matching the cleaneval frontier eval). Reward signal: binary code-correctness (1.0 if the generated program passes the problem's tests, otherwise 0.0). This checkpoint is the main revision (git branch) of the repo, with the model at the…

Excerpt from the card by Alexander Gurung.

Configuration

Architecture
Qwen3ForCausalLM
Context length (tokens)
262,144
Layers
36
Hidden size
2,560
Feed-forward size
9,728
Attention heads
32
Key/value heads
8
Head dimension
128
Vocabulary size
151,936
Model type
qwen3

Identity and Version

Repository
agurung/cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c
Publisher
Alexander Gurung
Task
Text generation
Modality
Text
Library
transformers
Parameters
4.4B parameters
Languages
Not stated by the source
Revision
ee8cf2fd4aa3d346ae70f38b2ad2ce6a82693fab
First published
2026-10-10
Last updated
2026-10-15

Files and Weights

7 files, 8.8 GB in total. The weights are 1 file totalling 8.8 GB in safetensors.

Weights1 file · 8.8 GB
Configuration2 files · 1.8 KB
Tokenizer2 files · 11.4 MB
Documentation1 file · 2.6 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights8.8 GB 7a047c63e5ca
config.jsonConfiguration1.6 KB —
generation_config.jsonConfiguration213 B —
README.mdDocumentation2.6 KB —
.gitattributesRepository1.6 KB —
tokenizer.jsonTokenizer11.4 MB be75606093db
tokenizer_config.jsonTokenizer694 B —

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
8.8 GB
Download from Alexander Gurung

Released by Alexander Gurung through its official repository on Hugging Face.

Built From

Memory Requirements

PrecisionWeights in memory
As published8.8 GB
16-bit8.8 GB
8-bit4.4 GB
4-bit2.2 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c

How much GPU memory does cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c need?

About 10.6 GB at 16-bit and 2.6 GB at 4-bit: the weights (4.4B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c 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 cobalt-seeded-rl-base-ramp25-stoppen-gen4k-ep2-ncp5-base-q3c's context length?

262,144 tokens, from the maximum position embeddings in its published configuration.

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