Laguna XS 2.1
Agentic coding model from Poolside in the XS size class for local deployment
- Context
- 262K
- Released
- 3mo ago
- Parameters
- —
- Input / 1M tokens
- $0.06
- Output / 1M tokens
- $0.12
- Cached input / 1M tokens
- $0.03
Sources:models.devOpenRouter
Benchmarks
DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.
Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.
No benchmark results have been matched to this model yet.
Specifications
- Developer
- Poolside
- Model family
- —
- Type
- Language model
- Predecessor
- —
- Successor
- —
- Released
- July 2, 2026
- Model ID
poolside/laguna-xs-2.1- Openness
- Open weights
- License
- —
- Parameters
- —
- Input modalities
- text
- Output modalities
- text
- Modality
- text->text
- Native context
- 256K
- Tokenizer
- Other
- Max output tokens
- 33K
- Hugging Face
- poolside/Laguna-XS-2.1
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- poolside/laguna-xs-2.1
- Source family
- laguna
- Last updated
- 2026-07-02
- Model context
- 262K
- Model output limit
- 33K
- Open weights
- Yes
- File attachments
- No
- Reasoning
- Yes
- Tool calling
- Yes
- Structured output
- No
- Temperature control
- Yes
Published benchmarks
Complete source record (JSON)
{
"id": "poolside/laguna-xs-2.1",
"name": "Laguna XS 2.1",
"description": "Agentic coding model from Poolside in the XS size class for local deployment",
"family": "laguna",
"last_updated": "2026-07-02",
"attachment": false,
"reasoning": true,
"tool_call": true,
"structured_output": false,
"temperature": true,
"modalities": {
"input": [
"text"
],
"output": [
"text"
]
},
"limit": {
"context": 262144,
"output": 32768
},
"benchmarks": [
{
"name": "SWE-Bench Verified",
"score": 70.9,
"source": "https://poolside.ai/blog/introducing-laguna-xs-2-1",
"metric": "resolved",
"harness": "Harbor",
"date": "2026-07-02"
},
{
"name": "SWE-Bench Multilingual",
"score": 63.1,
"source": "https://poolside.ai/blog/introducing-laguna-xs-2-1",
"metric": "resolve rate",
"harness": "Harbor",
"date": "2026-07-02"
},
{
"name": "SWE-Bench Pro",
"score": 47.6,
"source": "https://poolside.ai/blog/introducing-laguna-xs-2-1",
"metric": "resolve rate",
"harness": "Harbor",
"date": "2026-07-02"
},
{
"name": "Terminal-Bench",
"score": 37.5,
"source": "https://poolside.ai/blog/introducing-laguna-xs-2-1",
"metric": "success rate",
"harness": "Harbor",
"version": "2.0",
"date": "2026-07-02"
}
],
"release_date": "2026-07-02",
"open_weights": true
}Infrastructure
Provider availability
| Provider | Endpoint | Context | Input /M tokens | Output /M tokens | Cached input /M tokens | Cache write /M tokens | Uptime 1d | Data handling |
|---|---|---|---|---|---|---|---|---|
| poolside/fp8 | 262K | $0.06 | $0.12 | $0.03 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 |
Provider data:OpenRouter
Deployment graph
Can I run this?
Vertical Tabs only shows compatibility when it has structured evidence tying this exact model to hardware, runtime, quantization, memory use, and observed performance.