Marlin-2B
by NemoStation
2B video VLM with second-precise temporal captioning and grounding
NemoStation/Marlin-2Bmixpeek://image_extractor@v1/nemostation_marlin_2b_v1Overview
Marlin-2B is a 2-billion parameter video vision-language model from NemoStation that specializes in dense video captioning with second-level timestamp precision and temporal grounding. It tops the CaReBench leaderboard at the 2B scale and competes with models 3-4x its size on temporal understanding tasks. Built on Qwen3.5-2B, it processes video at 2 FPS with up to 240 frames, making it practical for production video indexing.
Architecture
Video VLM built on Qwen3.5-2B with a temporal-aware visual encoder. Processes video at 2 FPS sampling rate with a 240-frame cap (covering up to 2 minutes of video). Generates timestamped captions with [start:end] markers and supports temporal grounding queries that return specific time ranges.
Mixpeek SDK Integration
import { Mixpeek } from "mixpeek";
const mx = new Mixpeek({ apiKey: "API_KEY" });
// Managed: create a collection over a bucket; Mixpeek runs this model's extractor
const collection = await mx.collections.create({
namespace_id: "my-namespace",
collection_name: "my-collection",
source: { type: "bucket", bucket_ids: ["bkt_your_bucket"] },
feature_extractor: {
feature_extractor_name: "scene_caption",
version: "v1",
parameters: { model_id: "NemoStation/Marlin-2B" },
},
});Capabilities
- Dense video captioning with second-precise timestamps
- Temporal grounding — find specific moments from natural language queries
- Video summarization with temporal structure
- Scene transition detection and labeling
- Multi-event timeline generation from continuous video
Use Cases on Mixpeek
Benchmarks
| Dataset | Metric | Score | Source |
|---|---|---|---|
| CaReBench | Score | #1 at 2B scale | Competitive with 7B+ models |
| TimeLens-Bench | Temporal Acc | Matches Gemini-2.0-Flash | At 1/10th the parameter count |
Performance
Common Pipeline Companions
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Specification
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