Model Comparison

GLM-4.5V vs Qwen3-Next-80B-A3B-Instruct

Comparing GLM-4.5V and Qwen3-Next-80B-A3B-Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-4.5V and Qwen3-Next-80B-A3B-Instruct don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3-Next-80B-A3B-Instruct costs less

For input processing, GLM-4.5V ($0.55/1M tokens) is 3.7x more expensive than Qwen3-Next-80B-A3B-Instruct ($0.15/1M tokens).

For output processing, GLM-4.5V ($2.19/1M tokens) is 1.5x more expensive than Qwen3-Next-80B-A3B-Instruct ($1.50/1M tokens).

In conclusion, GLM-4.5V is more expensive than Qwen3-Next-80B-A3B-Instruct.*

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

Lowest available price from all providers

Mon Apr 20 2026 • llm-stats.com

GLM-4.5V

Input tokens$0.55

Output tokens$2.19

Best providerFireworks

Qwen3-Next-80B-A3B-Instruct

Input tokens$0.15

Output tokens$1.50

Best providerNovita

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

28.0B diff

GLM-4.5V has 28.0B more parameters than Qwen3-Next-80B-A3B-Instruct, making it 35.0% larger.

GLM-4.5V

108.0Bparameters

Qwen3-Next-80B-A3B-Instruct

80.0Bparameters

108.0B

GLM-4.5V

80.0B

Qwen3-Next-80B-A3B-Instruct

Context Window

Maximum input and output token capacity

GLM-4.5V accepts 131,072 input tokens compared to Qwen3-Next-80B-A3B-Instruct's 65,536 tokens. GLM-4.5V can generate longer responses up to 131,072 tokens, while Qwen3-Next-80B-A3B-Instruct is limited to 65,536 tokens.

GLM-4.5V

Input131,072 tokens

Output131,072 tokens

Qwen3-Next-80B-A3B-Instruct

Input65,536 tokens

Output65,536 tokens

Mon Apr 20 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-4.5V supports multimodal inputs, whereas Qwen3-Next-80B-A3B-Instruct does not.

GLM-4.5V can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.5V

Text

Images

Audio

Video

Qwen3-Next-80B-A3B-Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

GLM-4.5V is licensed under MIT, while Qwen3-Next-80B-A3B-Instruct uses Apache 2.0.

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

GLM-4.5V

MIT

Open weights

Qwen3-Next-80B-A3B-Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-4.5V was released on 2025-08-11, while Qwen3-Next-80B-A3B-Instruct was released on 2025-09-10.

Qwen3-Next-80B-A3B-Instruct is 1 month newer than GLM-4.5V.

GLM-4.5V

Aug 11, 2025

8 months ago

Qwen3-Next-80B-A3B-Instruct

Sep 10, 2025

7 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-4.5V is available from Fireworks, Novita. Qwen3-Next-80B-A3B-Instruct is available from Novita.

GLM-4.5V

Fireworks

Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M

Novita

Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M

Qwen3-Next-80B-A3B-Instruct

Novita

Input Price:Input: $0.15/1MOutput Price:Output: $1.50/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

GLM-4.5V

View details

Zhipu AI

Larger context window (131,072 tokens)

Supports multimodal inputs

Qwen3-Next-80B-A3B-Instruct

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens

Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature	GLM-4.5V	Qwen3-Next-80B-A3B-Instruct

FAQ

Common questions about GLM-4.5V vs Qwen3-Next-80B-A3B-Instruct

GLM-4.5V (Zhipu AI) and Qwen3-Next-80B-A3B-Instruct (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

Qwen3-Next-80B-A3B-Instruct scores MMLU-Redux: 90.9%, MultiPL-E: 87.8%, IFEval: 87.6%, WritingBench: 87.3%, Creative Writing v3: 85.3%.

Qwen3-Next-80B-A3B-Instruct is 3.7x cheaper for input tokens. GLM-4.5V costs $0.55/M input and $2.19/M output via fireworks. Qwen3-Next-80B-A3B-Instruct costs $0.15/M input and $1.50/M output via novita.

GLM-4.5V supports 131K tokens and Qwen3-Next-80B-A3B-Instruct supports 66K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Key differences include context window (131K vs 66K), input pricing ($0.55 vs $0.15/M), multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

GLM-4.5V is developed by Zhipu AI and Qwen3-Next-80B-A3B-Instruct is developed by Alibaba Cloud / Qwen Team.

GLM-4.5V vs Qwen3-Next-80B-A3B-Instruct

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

Input Capabilities

GLM-4.5V

Qwen3-Next-80B-A3B-Instruct

License

Release Timeline

Knowledge Cutoff

Provider Availability

GLM-4.5V

Qwen3-Next-80B-A3B-Instruct

Outputs Comparison

Key Takeaways

GLM-4.5V

Qwen3-Next-80B-A3B-Instruct

Detailed Comparison

FAQ

Which is better, GLM-4.5V or Qwen3-Next-80B-A3B-Instruct?

How does GLM-4.5V compare to Qwen3-Next-80B-A3B-Instruct in benchmarks?

Is GLM-4.5V cheaper than Qwen3-Next-80B-A3B-Instruct?

What are the context window sizes for GLM-4.5V and Qwen3-Next-80B-A3B-Instruct?

What are the main differences between GLM-4.5V and Qwen3-Next-80B-A3B-Instruct?

Who makes GLM-4.5V and Qwen3-Next-80B-A3B-Instruct?