Claude Sonnet 5 vs Qwen3.8-Next-Flash

Select two models to compare their coding performance, pricing, and features.

Key Takeaways

Coding tier: Claude Sonnet 5 has a higher reference index on the selected shared benchmark configuration than Qwen3.8-Next-Flash (105.06 vs 104.89, a 0.17-point difference). This does not by itself establish general coding superiority. Editorial tiers: Claude Sonnet 5 = A; Qwen3.8-Next-Flash = A. Tiers are separate editorial assessments and do not establish a reliable order within a tier.
API cost estimate: Estimated 1M in / 200K out tokens: $4.0000 (Claude Sonnet 5) vs $0.2440 (Qwen3.8-Next-Flash).
Metric Claude Sonnet 5 Qwen3.8-Next-Flash
Coding Index
105.06
104.89
Coding tier A A
Input Price $2/1M $0.15/1M
Output Price $10/1M $0.47/1M
Context Window 1M 1M

Coding Index

Coding Index · Reference baseline: 100

Claude Sonnet 5 105.06
Qwen3.8-Next-Flash 104.89

Integer index difference: 0.17

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

Claude Sonnet 5 Tier A

Qwen3.8-Next-Flash Tier A

Best For
  • •Coding assistance
  • •Document and codebase analysis
Strengths
  • •Text, image and video input
  • •Million-token context window

Claude Sonnet 5

OpenRouter quote 2026-10-11
Benchmark evidence and ranking method · Claude Sonnet 5

Cross-checked

Terminal-Bench 4.0 · Claude Code · max: 12.42% · 95% CI ± 3.06%

Artificial Analysis · Claude Sonnet 5 (Adaptive Reasoning, Max Effort)

Test configuration: max

Terminal-Bench 2.1: 80.52% · SciCode: 54.28%

LiveBench · 2026-06-25 · claude-sonnet-5-xhigh-effort

Coding: 80.68% · Agentic Coding: 59.39%

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

OpenRouter quote 2026-10-11
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):

Claude Sonnet 5: $4.0000

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: Claude Sonnet 5 or Qwen3.8-Next-Flash?

Claude Sonnet 5 has a higher reference index on the selected shared benchmark configuration than Qwen3.8-Next-Flash (105.06 vs 104.89, a 0.17-point difference). This does not by itself establish general coding superiority. Editorial tiers: Claude Sonnet 5 = A; Qwen3.8-Next-Flash = A. Tiers are separate editorial assessments and do not establish a reliable order within a tier.

How do Claude Sonnet 5 and Qwen3.8-Next-Flash compare in API pricing and costs?

Claude Sonnet 5: $2/1M input, $10/1M output (OpenRouter quote); Qwen3.8-Next-Flash: $0.15/1M input, $0.47/1M output (OpenRouter quote). 1M input + 200K output (USD): $4.0000 vs $0.2440.

What are the context window sizes of Claude Sonnet 5 and Qwen3.8-Next-Flash?

Claude Sonnet 5 provides a 1,000,000 token context window, while Qwen3.8-Next-Flash provides 1,000,000 tokens.

Try Claude Sonnet 5 → Try Qwen3.8-Next-Flash →