Laguna S 2.1 Free Is Now on OpenCode Zen — Why This Open-Weight Model Is a Big Deal
July 21, 2026
The Release
Poolside released Laguna S 2.1 today – and OpenCode added it to their Zen free endpoint within hours. OpenCode announced it with: “Laguna S 2.1 is now free on OpenCode, 1M Context, fully open source. Poolside’s most capable model to date.”
This is the kind of release that doesn’t make front-page news but actually matters for developers who build with AI agents.
The Specs
| Laguna S 2.1 | |
|---|---|
| Architecture | MoE (Mixture of Experts) |
| Total params | 118B |
| Active params | 8B per token |
| Context window | 1M tokens (1,048,576) |
| License | OpenMDW-1.1 (open-weight) |
| Released | July 21, 2026 |
| Available on | OpenCode Zen (free), OpenRouter (free), Hugging Face, Ollama |
| Local hardware | Runs on single DGX Spark (NVFP4 quantized) |
The headline stat: 8B active parameters. That’s tiny. For comparison, DeepSeek V4 Pro Max has 49B active. Claude Fable 5 has undisclosed but estimated 100B+. Nemotron 3 Ultra has 55B active.
Laguna S 2.1 does what it does with 8B active params. That’s the story.
Benchmarks
Here’s how it stacks up against models many times its size:
Terminal-Bench 2.1 (real-world terminal tasks)
| Model | Active Params | Score |
|---|---|---|
| Kimi K3 | 50B | 88.3 |
| Claude Fable 5 | ~100B+ | 88.0 |
| Laguna S 2.1 | 8B | 70.2 |
| Tencent Hy3 | 21B | 71.7 |
| Inkling | 41B | 63.8 |
| DeepSeek V4 Pro Max | 49B | 64.0 |
| Nemotron 3 Ultra | 55B | 56.4 |
Other Benchmarks
| Benchmark | Laguna S 2.1 | DeepSeek V4 Pro Max | Comparison |
|---|---|---|---|
| SWE-Bench Multilingual | 78.5 | 76.2 | +2.3 points |
| SWE-Bench Pro (Public) | 59.4 | 55.4 | +4 points |
| DeepSWE | 40.4 | 9.0 | +31.4 points |
| SWE Atlas (Codebase QnA) | 46.2 | 27.2 | +19 points |
| Toolathlon Verified | 49.7 | 55.9 | -6.2 points |
The DeepSWE score is the standout. Laguna S 2.1 crushes DeepSeek V4 Pro Max (40.4% vs 9.0%) despite having 6x fewer active parameters. DeepSWE tests real-world, long-horizon software engineering tasks – the kind of work coding agents actually do.
On SWE-Bench Multilingual, it even edges out Qwen 3.7 Max (78.3) and DeepSeek V4 Pro Max (76.2).
Why the Active Parameter Count Matters
MoE models only activate a fraction of their total parameters per token. Laguna S 2.1’s 8B active means:
- Fast inference – fewer params to compute per token
- Run locally – fits on consumer hardware with quantization
- Lower cost at scale – 8B active = 1/6th the compute of a 49B active model
- Free endpoint is sustainable – Poolside can offer free access because it’s cheap to serve
Poolside specifically mentions it runs on a single NVIDIA DGX Spark with the official NVFP4 quantized version. That’s a $3,000 desktop machine, not a data center.
Open Weights + Free API = Unusual
Most model releases give you either open weights or a free API, rarely both.
- Open weights on Hugging Face under OpenMDW-1.1 license
- Free on OpenCode Zen with full 1M context
- Free on OpenRouter with 262K context
- Available on Ollama for local runs
You can:
- Use it for free today through OpenCode or OpenRouter – no credit card needed
- Run it locally on a DGX Spark or similar through Ollama
- Fine-tune it since the weights are open
- Build products on it under the OpenMDW-1.1 license
This combination is rare for a model that scores 40%+ on DeepSWE.
How It Compares to Other Free Models
On OpenCode Zen, the free tier now includes:
| Model | Context | Best For |
|---|---|---|
| Big Pickle | N/A | General reasoning |
| Nemotron 3 Ultra | 1M | Heavy coding |
| DeepSeek V4 Flash | 1M | Speed |
| MiMo V2.5 | 1M | Multimodal |
| North Mini Code | 256K | Light tasks |
| Laguna S 2.1 | 1M | Agentic coding |
| Hy3 preview | 256K | Coding |
Laguna S 2.1 fills the “agentic coding” slot that was previously missing from the free tier. The 1M context on a free endpoint is also unusually generous.
The Timing
This launched on the same day as Gemini 3.6 Flash. Two coding model releases on the same day, but very different approaches:
- Gemini 3.6 Flash: Proprietary, API-only, $7.50/1M output, 49% DeepSWE
- Laguna S 2.1: Open-weight, free API, 8B active, 40.4% DeepSWE
For local/offline agent setups, Laguna S 2.1 is the more interesting option because you can actually run it yourself.
The Bottom Line
I switched my coding agent’s secondary model to Laguna S 2.1 on OpenCode Zen free to test it. For a model with 8B active parameters, the coding quality is surprising. The DeepSWE score against larger models suggests Poolside optimized specifically for the kind of work coding agents do – long tool call chains, debugging, multi-file edits.
If you run coding agents and haven’t tried it, it’s worth a test drive. Free endpoint, 1M context, no credit card. Hard to beat that price.
FAQs
Q: Is Laguna S 2.1 really free?
A: Yes. OpenCode Zen offers it free (no credit card needed). OpenRouter also has a free endpoint with 262K context. Both are legitimate free tiers, not trials.
Q: Can I run Laguna S 2.1 locally?
A: Yes. It’s on Ollama and Hugging Face. With 8B active params, it can run on a single high-memory machine. The official NVFP4 quantized version runs on a DGX Spark.
Q: How does it compare to DeepSeek V4 Flash?
A: Different strengths. DeepSeek V4 Flash is faster. Laguna S 2.1 is better at complex multi-step coding tasks and has a much higher DeepSWE score.
Q: What’s the license?
A: OpenMDW-1.1 from Poolside. Open-weight, allows commercial use. Check the license terms on Hugging Face for specifics.
Q: Is it better than Gemini 3.6 Flash?
A: On raw coding benchmarks, Gemini 3.6 Flash scores higher (49% vs 40.4% on DeepSWE). But Gemini is proprietary and costs $7.50/1M output. Laguna S 2.1 is open-weight and free. Different tools for different constraints.
Q: 8B active parameters seems small. Does it actually work well for complex tasks?
A: Yes – that’s the surprising part. The benchmarks show it beating models with 5-6x more active parameters. The MoE architecture lets it be small at inference time while retaining high capability.
Related: Gemini 3.6 Flash Released – also launched today. AI Agents for Developers – my current agent stack and how I choose models. OpenCode vs Claude Code – comparing the two coding agent platforms.