# GPT-5.5 vs Laguna M.1

> Side-by-side benchmark comparison for GPT-5.5 and Laguna M.1 across agentic, coding, multimodal, knowledge, reasoning, multilingual, and math tasks.

- Canonical page: https://benchlm.ai/compare/gpt-5-5-vs-laguna-m-1
- Last updated: September 10, 2026

- Shared sourced benchmarks: 8
- HTML indexing: indexable
- Ranking lane: BenchAlign v5

## Quick Verdict

Pick GPT-5.5 if you want the stronger benchmark profile. Laguna M.1 only makes more sense when its price, context window, or workload-specific category wins matter more than the overall score.

## Summary

- GPT-5.5 leads overall 72.07 to 3.93.
- The clearest category separation is in knowledge, where the averages are 72.9 for GPT-5.5 and 18.6 for Laguna M.1.
- The biggest single benchmark swing is GPQA Diamond (Vals) in Knowledge, with scores of 93.2% and 27.0%.
- Laguna M.1 is the cheaper option on output tokens, which matters if you expect large responses or heavy interactive use.
- GPT-5.5 also has the larger context window at 1M.

## Model Snapshot

| Property | GPT-5.5 | Laguna M.1 |
|----------|----------|----------|
| Creator | OpenAI | Poolside |
| Type | Proprietary | Proprietary |
| Reasoning | Reasoning | Reasoning |
| Context | 1M | 256K |
| Overall Score | 72.07 | 3.93 |
| Benchmarks Covered | 38 | 10 |
| Pricing (input/output) | $5.00 / $30.00 | Pricing unavailable / Pricing unavailable |

## Category Breakdown

### Agentic

- Winner: Coming soon
- GPT-5.5 public-lane score: 61 (Supported · #17/152)
- Laguna M.1 public-lane score: 23.9 (Estimated · #147/152)

| Benchmark | GPT-5.5 | Laguna M.1 | Winner |
|-----------|-----------|-----------|--------|
| Terminal-Bench 2.0 | 82% | 45.8% | GPT-5.5 |
| CyberGym | 81.8% | Coming soon | Coming soon |
| BrowseComp | 84.4% | Coming soon | Coming soon |
| OSWorld-Verified | 78.7% | Coming soon | Coming soon |
| MCP Atlas | 75.3% | Coming soon | Coming soon |
| Toolathlon | 55.6% | Coming soon | Coming soon |
| τ²-bench results | 98% | Coming soon | Coming soon |
| Gert Labs | 72.93% | Coming soon | Coming soon |
| ResearchClawBench | 17.0% | Coming soon | Coming soon |
| OSWorld 2.0 | 13.0% | Coming soon | Coming soon |
| JobBench | 42.7% | Coming soon | Coming soon |
| ExploitGym | 13.4% | Coming soon | Coming soon |
| Terminal-Bench 2.1 (Vals) | 76.4% | 34.1% | GPT-5.5 |

### Coding

- Winner: GPT-5.5
- GPT-5.5 public-lane score: 67.6 (Supported · #7/151)
- Laguna M.1 public-lane score: 29.7 (Supported · #140/151)

| Benchmark | GPT-5.5 | Laguna M.1 | Winner |
|-----------|-----------|-----------|--------|
| SWE-bench Pro | 58.6% | 49.2% | GPT-5.5 |
| Terminal-Bench 2.0 | 82.0% | 45.8% | GPT-5.5 |
| Vibe Code Bench | 69.85% | Coming soon | Coming soon |
| React Native Evals | 84.7% | Coming soon | Coming soon |
| cursorBench31 | 59.2% | Coming soon | Coming soon |
| cursorBench32 | 58.4% | Coming soon | Coming soon |
| FrontierCode 1.1 Main | 43.0% | Coming soon | Coming soon |
| LiveCodeBench (Vals) | 85.3% | 68.1% | GPT-5.5 |
| SWE-bench (Vals) | 82.6% | 57.6% | GPT-5.5 |
| SWE-bench Verified | Coming soon | 74.6% | Coming soon |
| SWE Multilingual | Coming soon | 63.1% | Coming soon |

### Multimodal & Grounded

- Winner: Coming soon
- GPT-5.5 public-lane score: 71.3 (#19/48)
- Laguna M.1 public-lane score: Coming soon

| Benchmark | GPT-5.5 | Laguna M.1 | Winner |
|-----------|-----------|-----------|--------|
| MMMU-Pro | 81.2% | Coming soon | Coming soon |
| MMMU-Pro w/ Python | 83.2% | Coming soon | Coming soon |
| OfficeQA Pro | 54.1% | Coming soon | Coming soon |

### Reasoning

- Winner: Coming soon
- GPT-5.5 public-lane score: 64 (#13/20)
- Laguna M.1 public-lane score: Coming soon

| Benchmark | GPT-5.5 | Laguna M.1 | Winner |
|-----------|-----------|-----------|--------|
| MRCR v2 64K-128K | 83.1% | Coming soon | Coming soon |
| MRCR v2 128K-256K | 87.5% | Coming soon | Coming soon |
| ARC-AGI-2 | 85% | Coming soon | Coming soon |
| ARC-AGI-3 | 0.4% | Coming soon | Coming soon |

### Knowledge

- Winner: Coming soon
- GPT-5.5 public-lane score: 72.9 (Supported · #7/183)
- Laguna M.1 public-lane score: 18.6 (Estimated · #182/183)

| Benchmark | GPT-5.5 | Laguna M.1 | Winner |
|-----------|-----------|-----------|--------|
| GPQA | 93.6% | Coming soon | Coming soon |
| GPQA-D | 93.6% | Coming soon | Coming soon |
| HLE | 52.2% | Coming soon | Coming soon |
| HLE w/o tools | 41.4% | Coming soon | Coming soon |
| GPQA Diamond (Vals) | 93.2% | 27.0% | GPT-5.5 |
| MMLU-Pro (Vals) | 88.1% | 68.8% | GPT-5.5 |

### Instruction Following

- Winner: Coming soon
- GPT-5.5 public-lane score: 93.2 (#7/123)
- Laguna M.1 public-lane score: Coming soon

### Mathematics

- Winner: Coming soon
- GPT-5.5 public-lane score: 69.6 (Unranked · 3 rankable rows)
- Laguna M.1 public-lane score: Coming soon

| Benchmark | GPT-5.5 | Laguna M.1 | Winner |
|-----------|-----------|-----------|--------|
| FrontierMath (legacy) | 51.7% | Coming soon | Coming soon |
| FrontierMath v2 (Tiers 1-3) | 51.700% | Coming soon | Coming soon |
| FrontierMath v2 (Tier 4) | 35.400% | Coming soon | Coming soon |

## FAQ

### Which is better overall, GPT-5.5 or Laguna M.1?

GPT-5.5 is ahead overall on BenchLM right now.

### Where is the biggest gap between GPT-5.5 and Laguna M.1?

The widest category gap is in knowledge, where the averages are 72.9 for GPT-5.5 and 18.6 for Laguna M.1.

### How many benchmarks does GPT-5.5 cover on BenchLM?

GPT-5.5 currently has 38 sourced benchmark scores on BenchLM.

### How many benchmarks does Laguna M.1 cover on BenchLM?

Laguna M.1 currently has 10 sourced benchmark scores on BenchLM.

## Related Comparisons

- [GPT-5.5 vs GPT-5.5 Pro](/compare/gpt-5-5-vs-gpt-5-5-pro)
- [Laguna M.1 vs GPT-5.5 Pro](/compare/gpt-5-5-pro-vs-laguna-m-1)
- [GPT-5.5 vs Laguna XS.2](/compare/gpt-5-5-vs-laguna-xs-2)
- [Laguna M.1 vs Laguna XS.2](/compare/laguna-m-1-vs-laguna-xs-2)

## Explore More

- [GPT-5.5 profile](/models/gpt-5-5)
- [Laguna M.1 profile](/models/laguna-m-1)
- [Compare Pricing](/llm-pricing)
- [Alternative Finder](/tools/alternative-finder)
- [LLM Selector](/tools/llm-selector)
- [Overall Rankings](/best/overall)