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GLM-5.2 vs Laguna S 2.1

GLM-5.2 and Laguna S 2.1 are closely matched at 46.5 and 41.4 on the LLM Stats Score. Laguna S 2.1 is 11.7x cheaper per token.

Zhipu AI · Poolside · Updated for 2026

Which is better?

GLM-5.2 and Laguna S 2.1 are closely matched on the overall LLM Stats Score at 46.5 and 41.4.

In the 4 individual benchmarks reported for both models, GLM-5.2 wins 3; this is a narrower head-to-head signal than the composite indexes.

On price, Laguna S 2.1 is roughly 11.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GLM-5.2

  • you value its reported benchmark strengths — it wins 3 of 4 exact shared results

Choose Laguna S 2.1

  • cost matters — it's about 11.7x cheaper per token
  • you want the most recent training data — it shipped Jul 2026

At a glance

The differences that matter most.

Core performance indexes
46.5
#22
41.4
#43
45.8
#22
41.5
#40
38.1
#21
33.1
#37
32.0
#25
25.7
#43
Cost, coverage & limits
Benchmark wins
3 of 4
1 of 4
Input price
$0.95 / M
$0.10 / M
Output price
$3.00 / M
$0.20 / M
Context window
1,048,576
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GLM-5.2
Laguna S 2.1
23.6#36
18.9#56
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for GLM-5.2 · 6 for Laguna S 2.1

4 shared

GLM-5.2 outperforms in 3 benchmarks (DeepSWE 1.1, SWE-Bench Pro, Terminal-Bench 2.1), while Laguna S 2.1 is better at 1 benchmark (Toolathlon).

GLM-5.2 shows notably better performance in the majority of benchmarks.

Fri Aug 28 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Laguna S 2.1 costs less

For input processing, GLM-5.2 ($0.95/1M tokens) is 9.5x more expensive than Laguna S 2.1 ($0.10/1M tokens).

For output processing, GLM-5.2 ($3.00/1M tokens) is 15.0x more expensive than Laguna S 2.1 ($0.20/1M tokens).

In conclusion, GLM-5.2 is more expensive than Laguna S 2.1.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Aug 28 2026 • llm-stats.com
Zhipu AI
GLM-5.2
Input tokens$0.95
Output tokens$3.00
Best providerDeepinfra
Poolside
Laguna S 2.1
Input tokens$0.10
Output tokens$0.20
Best providerPoolside
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

635.0B diff

GLM-5.2 has 635.0B more parameters than Laguna S 2.1, making it 538.1% larger.

Zhipu AI
GLM-5.2
753.0Bparameters
Poolside
Laguna S 2.1
118.0Bparameters
753.0B
GLM-5.2
118.0B
Laguna S 2.1

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,048,576 tokens. Only GLM-5.2 specifies output context (131,072 tokens).

Zhipu AI
GLM-5.2
Input1,048,576 tokens
Output131,072 tokens
Poolside
Laguna S 2.1
Input1,048,576 tokens
Output- tokens
Fri Aug 28 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5.2 is licensed under MIT, while Laguna S 2.1 uses OpenMDW License v1.1.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-5.2

MIT

Open weights

Laguna S 2.1

OpenMDW License v1.1

Open weights

Release Timeline

When each model was launched

GLM-5.2 was released on 2026-06-16, while Laguna S 2.1 was released on 2026-07-21.

Laguna S 2.1 is 1 month newer than GLM-5.2.

GLM-5.2

Jun 16, 2026

2 months ago

Laguna S 2.1

Jul 21, 2026

1 months ago

1mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI. Laguna S 2.1 is available from Poolside.

GLM-5.2

deepinfra logo
Deepinfra
Input Price:Input: $0.95/1MOutput Price:Output: $3.00/1M
fireworks logo
Fireworks
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
friendli logo
FriendliAI
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
novita logo
Novita
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
together logo
Together
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
z logo
Unknown Organization
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M

Laguna S 2.1

poolside logo
Poolside
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GLM-5.2 and Laguna S 2.1 side-by-side, then vote on the output you prefer.

GLM-5.2
✓ Preferred
Laguna S 2.1
Open in Playground

FAQ

Common questions about GLM-5.2 vs Laguna S 2.1.

Which is better, GLM-5.2 or Laguna S 2.1?

GLM-5.2 and Laguna S 2.1 are closely matched on the LLM Stats Score at 46.5 and 41.4. GLM-5.2 is made by Zhipu AI and Laguna S 2.1 is made by Poolside. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-5.2 compare to Laguna S 2.1 in benchmarks?

GLM-5.2 scores AIME 2026: 99.2%, HMMT 2025: 94.4%, HMMT Feb 26: 92.5%, GPQA: 91.2%, IMO-AnswerBench: 91.0%. Laguna S 2.1 scores SWE-bench Multilingual: 78.5%, Terminal-Bench 2.1: 70.2%, SWE-Bench Pro: 59.4%, Toolathlon: 49.7%, SWE Atlas - Codebase QnA: 46.2%.

Is GLM-5.2 cheaper than Laguna S 2.1?

Laguna S 2.1 is 9.5x cheaper for input tokens. GLM-5.2 costs $0.95/M input and $3.00/M output via deepinfra. Laguna S 2.1 costs $0.10/M input and $0.20/M output via poolside.

What are the context window sizes for GLM-5.2 and Laguna S 2.1?

GLM-5.2 supports 1.0M tokens and Laguna S 2.1 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-5.2 and Laguna S 2.1?

Key differences include LLM Stats Score (46.5 vs 41.4), input pricing ($0.95 vs $0.10/M), licensing (MIT vs OpenMDW License v1.1). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.2 and Laguna S 2.1?

GLM-5.2 is developed by Zhipu AI and Laguna S 2.1 is developed by Poolside.