IDES & CODING TOOLS • CURATED • UPDATED SEP 1, 2026

Laguna S 2.1

118B MoE model beats rivals 10x its size on coding benchmarks
Price
Free
API
No
Weights
Yes

Laguna S 2.1 is a 118 billion parameter Mixture-of-Experts model from Poolside AI, released August 2026. Activates only 8 billion parameters per token, supports context windows up to 1 million tokens, runs under permissive OpenMDW-1.1 license. Benchmarks: 70.2% on Terminal-Bench 2.1 (beating DeepSeek-V4-Pro-Max, Nvidia Nemotron 3 Ultra), 78.5% on SWE-Bench Multilingual. Trained in under 9 weeks on 4,096 Nvidia H200 GPUs.

Benchmark contender: claims to beat models many times its size on two critical coding benchmarks. Open weights under permissive license. Rapid training timeline (9 weeks) suggests efficient engineering. Strong SWE-Bench showing makes it worth evaluating for coding agent workloads.

Pricing Free
Platforms local
API No
Open Source Yes
Modalities IDEs & Coding Tools, LLMs
Best For Best for Coding Performance
Date Added 2026-09-01
  • ✓70.2% on Terminal-Bench 2.1 (beats larger closed models)
  • ✓78.5% on SWE-Bench Multilingual
  • ✓1M token context window
  • ✓Efficient MoE: 118B total / 8B active per token
  • ✓OpenMDW-1.1 permissive license

Download weights from Hugging Face. Use vLLM or llama.cpp with MoE support. Quantize to 4-bit for consumer GPUs using bitsandbytes.

Terminal-Bench SWE Challenge Solving

Solve competitive programming challenges with reasoning and code generation.

STEPS:
  1. Load Laguna S 2.1 with vLLM
  2. Feed problem statement to 1M context window
  3. Generate solution with benchmark-proven accuracy
  4. Verify against test cases

Long-Context Code Review

Review entire codebases using 1M token context for architectural understanding.

STEPS:
  1. Concatenate repository files (under 1M tokens)
  2. Request architectural analysis
  3. Get cross-file impact analysis
  4. Identify long-range dependency issues

Multilingual SWE-Bench Tasks

Solve engineering tasks across multiple programming languages.

STEPS:
  1. Submit multilingual codebase
  2. Request SWE-Bench-style completion
  3. Get 78.5% accuracy on multilingual tasks
  4. Validate completions match expected behavior
Free Completely free
View Laguna S 2.1 Alternatives (2026) →

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Q

Is Laguna S 2.1 free?

A

Yes, Laguna S 2.1 is completely free to use.

Q

Does Laguna S 2.1 have an API?

A

No, Laguna S 2.1 does not appear to offer a public API.

Q

What is Laguna S 2.1 best for?

A

Laguna S 2.1 is best for Coding Performance. Laguna S 2. Benchmark contender: claims to beat models many times its size on two critical coding benchmarks. Open weights under permissive license. Rapid training timeline (9 weeks) suggests efficient engineering. Strong SWE-Bench showing makes it worth evaluating for coding agent workloads.

Q

What platforms does Laguna S 2.1 support?

A

Laguna S 2.1 supports local.

Q

Is Laguna S 2.1 open source?

A

Yes, Laguna S 2.1 is open source. You can access the source code on GitHub at https://github.com/poolside-ai/laguna.

Q

How do I get started with Laguna S 2.1?

A

Download weights from Hugging Face. Use vLLM or llama.cpp with MoE support. Quantize to 4-bit for consumer GPUs using bitsandbytes.

Q

How do I use Laguna S 2.1?

A

Laguna S 2.1 is a large language model for text generation, analysis, and conversation. Use through available interfaces. Enter prompts or questions to get responses. It excels at 70.2% on terminal-bench 2.1 (beats larger closed models).

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