GLM-5.3-Flash vs Qwen3.8-Next-Flash
Select two models to compare their coding performance, pricing, and features.
Key Takeaways
| Metric | GLM-5.3-Flash | Qwen3.8-Next-Flash |
|---|---|---|
| Coding Index | 104.81 | 104.89 |
| Coding tier | A | A |
| Input Price | $0.15/1M | $0.15/1M |
| Output Price | $0.5/1M | $0.47/1M |
| Context Window | 1.05M | 1M |
Coding Index
Coding Index · Reference baseline: 100
Integer index difference: 0.08
DeepSeek V4 Flash 0731 = 100. The index reflects two shared tests, not capability multiples or statistically established gaps.
Verdict
Both models share an editorial tier. The evidence does not establish a reliable order within it; compare them on your own projects.
Capabilities & Use Cases Comparison
GLM-5.3-Flash Tier A
- •Coding assistance
- •Long-context analysis
- •Native multimodal input
- •Long-context coding and agent tasks
Qwen3.8-Next-Flash Tier A
- •Coding assistance
- •Document and codebase analysis
- •Text, image and video input
- •Million-token context window
GLM-5.3-Flash
Benchmark evidence and ranking method · GLM-5.3-Flash
Cross-checked
Artificial Analysis · GLM-5.3-Flash
Test configuration: max
Terminal-Bench 2.1: 84.27% · SciCode: 51.62%
LiveBench · 2026-06-25 · glm-5.3-flash
Coding: 78.95% · Agentic Coding: 56.77%
ModelRank assigns editorial tiers using public coding evidence, not automatic index thresholds or statistically proven classes. Price, speed, context size and sponsorship do not affect tiers.
DeepSeek V4 Flash 0731 = 100. The index reflects two shared tests, not capability multiples or statistically established gaps.
Results reflect particular model configurations. Agent harnesses, reasoning effort, tools, budgets and tasks may differ. Close indices do not establish superiority. B describes a relative position in this selected group, not an inability to code.
Data checked: 2026-09-10. Snapshot date is the retrieval date, not necessarily the evaluation date.
Qwen3.8-Next-Flash
Benchmark evidence and ranking method · Qwen3.8-Next-Flash
Cross-checked
Artificial Analysis · Qwen3.8-Flash-Next
Test configuration: unspecified
Terminal-Bench 2.1: 86.14% · SciCode: 50.58%
LiveBench · 2026-06-25 · qwen3.8-flash-next
Coding: 72.55% · Agentic Coding: 61.62%
ModelRank assigns editorial tiers using public coding evidence, not automatic index thresholds or statistically proven classes. Price, speed, context size and sponsorship do not affect tiers.
DeepSeek V4 Flash 0731 = 100. The index reflects two shared tests, not capability multiples or statistically established gaps.
Results reflect particular model configurations. Agent harnesses, reasoning effort, tools, budgets and tasks may differ. Close indices do not establish superiority. B describes a relative position in this selected group, not an inability to code.
Data checked: 2026-09-10. Snapshot date is the retrieval date, not necessarily the evaluation date.
Results reflect particular model configurations. Agent harnesses, reasoning effort, tools, budgets and tasks may differ. Close indices do not establish superiority. B describes a relative position in this selected group, not an inability to code.
API cost estimate
1M input + 200K output (USD):
GLM-5.3-Flash: $0.2500
Qwen3.8-Next-Flash: $0.2440
Estimates use the displayed channel and time band; DeepSeek uses peak rates. Cache discounts, tool fees, long-context price tiers and uncounted additional tokens are excluded.
Frequently Asked Questions
Which model is better for coding: GLM-5.3-Flash or Qwen3.8-Next-Flash?
Qwen3.8-Next-Flash has a higher reference index on the selected shared benchmark configuration than GLM-5.3-Flash (104.89 vs 104.81, a 0.08-point difference). This does not by itself establish general coding superiority. Editorial tiers: GLM-5.3-Flash = A; Qwen3.8-Next-Flash = A. Tiers are separate editorial assessments and do not establish a reliable order within a tier.
How do GLM-5.3-Flash and Qwen3.8-Next-Flash compare in API pricing and costs?
GLM-5.3-Flash: $0.15/1M input, $0.5/1M output (OpenRouter quote); Qwen3.8-Next-Flash: $0.15/1M input, $0.47/1M output (OpenRouter quote). 1M input + 200K output (USD): $0.2500 vs $0.2440.
What are the context window sizes of GLM-5.3-Flash and Qwen3.8-Next-Flash?
GLM-5.3-Flash provides a 1,048,576 token context window, while Qwen3.8-Next-Flash provides 1,000,000 tokens.