Model decision surface
Compare AI models
Start with Ling-3.0-flash and Qwen3 Coder Next, or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.
Current public data
Ling-3.0-flash vs Qwen3 Coder Next
Live dataset updated 9/3/2026, 3:06:08 AM UTC
Open 1200×630 evidence receipt| Field | Ling-3.0-flash InclusionAI | Qwen3 Coder Next Qwen |
|---|---|---|
| ModelCap position | #49 | #91 |
| Index score | 51.7 | 28.0 |
| Evidence | Measured1 public benchmark observation across 1 board | Measured1 public benchmark observation across 1 board |
| Input / 1M | $0.021 | $0.12 |
| Output / 1M | $0.063 | $0.80 |
| Pricing status | fresh | fresh |
| Context | 262K | 262K |
| Providers | 2 | 4 |
| Weight access | Open weights | Open weights |
Decision facts
- Ling-3.0-flash is #49; Qwen3 Coder Next is #91 on the same current language board.
- Index scores are 51.7 for Ling-3.0-flash and 28.0 for Qwen3 Coder Next.
- Both positions use Measured evidence.
- Listed output price per 1M tokens is $0.06 for Ling-3.0-flash and $0.80 for Qwen3 Coder Next.
- Published context is 262,144 tokens for Ling-3.0-flash and 262,144 for Qwen3 Coder Next.
- ModelCap currently lists 2 providers for Ling-3.0-flash and 4 for Qwen3 Coder Next.
These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.
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Each comparison page is a permanent, shareable URL with the same live figures as this tool: ModelCap Index position, API pricing, context window, provider count, weight access and every shared benchmark board.