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GLM-4.5 vs Ling 3.1 Flash

Ling 3.1 Flash leads the LLM Stats Score 51.0 to 27.6.

Zhipu AI · InclusionAI · Updated for 2026

Which is better?

Ling 3.1 Flash leads the overall LLM Stats Score 51.0 to 27.6, ranking #15 overall.

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

Choose GLM-4.5

  • you need open weights you can self-host or fine-tune

Choose Ling 3.1 Flash

  • overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

GLM-4.5
Zhipu AI
Ling 3.1 Flash
InclusionAI
Core performance indexes
LLM Stats Score
27.6
#155
51.0
#15
Reasoning
27.1
#156
47.5
#26
Coding
15.7
#141
38.8
#18
Agents
9.8
#135
38.0
#12
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.40 / M
— / M
Output price
$1.60 / M
— / M
Context window
131,072
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GLM-4.5
Ling 3.1 Flash
Tool use
21.3#54
29.0#16
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for GLM-4.5 · 11 for Ling 3.1 Flash

No common benchmarks found

GLM-4.5 and Ling 3.1 Flashdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

205.0B diff

Ling 3.1 Flash has 205.0B more parameters than GLM-4.5, making it 57.7% larger.

Zhipu AI
GLM-4.5
355.0Bparameters
InclusionAI
Ling 3.1 Flash
560.0Bparameters
355.0B
GLM-4.5
560.0B
Ling 3.1 Flash

Context Window

Maximum input and output token capacity

Only GLM-4.5 specifies input context (131,072 tokens). Only GLM-4.5 specifies output context (131,072 tokens).

Zhipu AI
GLM-4.5
Input131,072 tokens
Output131,072 tokens
InclusionAI
Ling 3.1 Flash
Input- tokens
Output- tokens
Fri Oct 09 2026 • llm-stats.com

Release Timeline

When each model was launched

GLM-4.5 was released on 2025-07-28, while Ling 3.1 Flash was released on 2026-09-30.

Ling 3.1 Flash is 14 months newer than GLM-4.5.

GLM-4.5

Jul 28, 2025

1.2 years ago

Ling 3.1 Flash

Sep 30, 2026

1 weeks ago

1.2yr 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

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against GLM-4.5 and Ling 3.1 Flash side-by-side, then vote on the output you prefer.

GLM-4.5
✓ Preferred
Ling 3.1 Flash
Open in Playground

FAQ

Common questions about GLM-4.5 vs Ling 3.1 Flash.

Which is better, GLM-4.5 or Ling 3.1 Flash?

Ling 3.1 Flash leads the LLM Stats Score 51.0 to 27.6. GLM-4.5 is made by Zhipu AI and Ling 3.1 Flash is made by InclusionAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GLM-4.5 compare to Ling 3.1 Flash in benchmarks?

GLM-4.5 scores MATH-500: 98.2%, AIME 2024: 91.0%, MMLU-Pro: 84.6%, TAU-bench Retail: 79.7%, GPQA: 79.1%. Ling 3.1 Flash scores CyberGym: 87.9%, DRACO: 85.5%, FrontierSWE: 75.2%, Multi-Challenge: 69.8%, SkillsBench: 68.7%.

What are the context window sizes for GLM-4.5 and Ling 3.1 Flash?

GLM-4.5 supports 131K tokens and Ling 3.1 Flash supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-4.5 and Ling 3.1 Flash?

Key differences include LLM Stats Score (27.6 vs 51.0), licensing (MIT vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.5 and Ling 3.1 Flash?

GLM-4.5 is developed by Zhipu AI and Ling 3.1 Flash is developed by InclusionAI.

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