GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct: The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct Showdown

After a comprehensive analysis, GLM-4.6V (Reasoning) emerges as the superior choice for users prioritizing raw intelligence and reasoning. However, Qwen3 VL 8B Instruct remains a highly competitive option, especially for scenarios demanding faster response times and cost-efficiency. This detailed GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct comparison will break down every critical metric to help you make the best decision.

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Model Snapshot

Key decision metrics at a glance.

GLM-4.6V (Reasoning)

Other

Reasoning: 9
Coding: 2
Multimodal: 2
Long Context: 3
Blended Price / 1M tokens: $0.000
P95 Latency: 1000ms
Tokens per second: 74.022tokens/sec

Qwen3 VL 8B Instruct

Other

Reasoning: 3
Coding: 1
Multimodal: 1
Long Context: 2
Blended Price / 1M tokens: $0.000
P95 Latency: 1000ms
Tokens per second: 99.366tokens/sec

Overall Capabilities

The capability radar provides a holistic view of the GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct matchup. This chart illustrates each model's strengths and weaknesses at a glance, forming a cornerstone of our GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct analysis.

This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `GLM-4.6V (Reasoning)` vs `Qwen3 VL 8B Instruct`.

Benchmark Breakdown

For a granular look, this chart directly compares scores across standardized benchmarks. In the critical MMLU Pro test, a key part of the GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct debate, GLM-4.6V (Reasoning) scores 90 against Qwen3 VL 8B Instruct's 30. This data-driven approach is essential for any serious GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct comparison.

This grouped bar chart provides a side-by-side comparison for each benchmark metric.

Speed & Latency

Speed is a crucial factor in the GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct decision for interactive applications. The metrics below highlight the trade-offs you should weigh before shipping to production.

Time to First Token

GLM-4.6V (Reasoning)300ms

Qwen3 VL 8B Instruct300ms

Tokens per Second

GLM-4.6V (Reasoning)74.022

Qwen3 VL 8B Instruct99.366

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The Economics of GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct

Power is only one part of the equation. This GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct pricing analysis gives you a true sense of value.

Pricing Breakdown

Compare input and output pricing at a glance.

Real-World Cost Scenario

To process 1M input tokens and generate 250k output tokens, GLM-4.6V (Reasoning) would cost $0.001, whereas Qwen3 VL 8B Instruct would cost $0.000. This practical calculation is vital for any developer considering the GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct choice.

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Which Model Wins the GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct Battle for You?

Choose GLM-4.6V (Reasoning) if...

Your top priority is raw performance and capability.

You are working in a technical or scientific field requiring the highest accuracy.

Cost is a secondary concern to power in your GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct decision.

Choose Qwen3 VL 8B Instruct if...

You need a highly responsive model for user-facing applications.

Your budget is a primary consideration in the GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct choice.

You are developing at scale where operational costs are critical.

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Your Questions about the GLM-4.6V (Reasoning) vs Qwen3 VL 8B Instruct Comparison

Review the full evaluation methodology · Read the latest analysis posts

Data source: https://artificialanalysis.ai/