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GLM-4.7 vs Ling 3.1 Flash

Ling 3.1 Flash leads the LLM Stats Score 51.0 to 34.2.

Zhipu AI · InclusionAI · Updated for 2026

Which is better?

Ling 3.1 Flash leads the overall LLM Stats Score 51.0 to 34.2, ranking #15 overall.

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

Choose GLM-4.7

  • 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-4.7
Zhipu AI
Ling 3.1 Flash
InclusionAI
Core performance indexes
LLM Stats Score
34.2
#105
51.0
#15
Reasoning
34.1
#101
47.5
#26
Coding
17.4
#130
38.8
#18
Agents
9.4
#137
38.0
#12
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.40 / M
— / M
Output price
$1.75 / M
— / M
Context window
202,752
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
GLM-4.7
Ling 3.1 Flash
Tool use
8.3#150
29.0#16
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

13 reported for GLM-4.7 · 11 for Ling 3.1 Flash

No common benchmarks found

GLM-4.7 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

202.0B diff

Ling 3.1 Flash has 202.0B more parameters than GLM-4.7, making it 56.4% larger.

Zhipu AI
GLM-4.7
358.0Bparameters
InclusionAI
Ling 3.1 Flash
560.0Bparameters
358.0B
GLM-4.7
560.0B
Ling 3.1 Flash

Context Window

Maximum input and output token capacity

Only GLM-4.7 specifies input context (202,752 tokens). Only GLM-4.7 specifies output context (202,752 tokens).

Zhipu AI
GLM-4.7
Input202,752 tokens
Output202,752 tokens
InclusionAI
Ling 3.1 Flash
Input- tokens
Output- tokens
Fri Oct 09 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GLM-4.7 supports multimodal inputs, whereas Ling 3.1 Flash does not.

GLM-4.7 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.7

Text
Images
Audio
Video

Ling 3.1 Flash

Text
Images
Audio
Video

Release Timeline

When each model was launched

GLM-4.7 was released on 2025-12-22, while Ling 3.1 Flash was released on 2026-09-30.

Ling 3.1 Flash is 9 months newer than GLM-4.7.

GLM-4.7

Dec 22, 2025

9 months ago

Ling 3.1 Flash

Sep 30, 2026

1 weeks ago

9mo 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-4.7 and Ling 3.1 Flash side-by-side, then vote on the output you prefer.

GLM-4.7
✓ Preferred
Ling 3.1 Flash
Open in Playground

FAQ

Common questions about GLM-4.7 vs Ling 3.1 Flash.

Which is better, GLM-4.7 or Ling 3.1 Flash?

Ling 3.1 Flash leads the LLM Stats Score 51.0 to 34.2. GLM-4.7 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-4.7 compare to Ling 3.1 Flash in benchmarks?

GLM-4.7 scores AIME 2025: 95.7%, Tau-bench: 87.4%, GPQA: 85.7%, LiveCodeBench v6: 84.9%, MMLU-Pro: 84.3%. 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-4.7 and Ling 3.1 Flash?

GLM-4.7 supports 203K 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-4.7 and Ling 3.1 Flash?

Key differences include LLM Stats Score (34.2 vs 51.0), multimodal support (yes vs no), licensing (MIT vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.7 and Ling 3.1 Flash?

GLM-4.7 is developed by Zhipu AI and Ling 3.1 Flash is developed by InclusionAI.

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